Triple
T4325292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pallets Projects |
E96621
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
MarkupSafe
MarkupSafe is a Python library that provides a string type with automatic HTML escaping, commonly used in web templating to prevent injection vulnerabilities.
|
E431942
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: MarkupSafe | Statement: [Pallets Projects, notableWork, MarkupSafe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MarkupSafe Context triple: [Pallets Projects, notableWork, MarkupSafe]
-
A.
Jinja2
Jinja2 is a popular Python templating engine used to generate dynamic HTML and other text-based formats, known for its Django-inspired syntax and integration with web frameworks like Flask.
-
B.
Jinja
Jinja is a major town in southeastern Uganda, known as a key industrial center and a popular tourist destination near the source of the Nile River.
-
C.
CSP
CSP is the commonly used abbreviation for the Conference of the States Parties, the main decision-making body overseeing implementation of the Chemical Weapons Convention.
-
D.
PEP 636
PEP 636 is a Python Enhancement Proposal that serves as a tutorial-style guide to the structural pattern matching feature introduced in Python 3.10.
-
E.
PEP 622
PEP 622 is a Python Enhancement Proposal that introduced the design for structural pattern matching syntax later adopted in Python 3.10.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: MarkupSafe Triple: [Pallets Projects, notableWork, MarkupSafe]
Generated description
MarkupSafe is a Python library that provides a string type with automatic HTML escaping, commonly used in web templating to prevent injection vulnerabilities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MarkupSafe Target entity description: MarkupSafe is a Python library that provides a string type with automatic HTML escaping, commonly used in web templating to prevent injection vulnerabilities.
-
A.
Jinja2
Jinja2 is a popular Python templating engine used to generate dynamic HTML and other text-based formats, known for its Django-inspired syntax and integration with web frameworks like Flask.
-
B.
Jinja
Jinja is a major town in southeastern Uganda, known as a key industrial center and a popular tourist destination near the source of the Nile River.
-
C.
CSP
CSP is the commonly used abbreviation for the Conference of the States Parties, the main decision-making body overseeing implementation of the Chemical Weapons Convention.
-
D.
PEP 636
PEP 636 is a Python Enhancement Proposal that serves as a tutorial-style guide to the structural pattern matching feature introduced in Python 3.10.
-
E.
PEP 622
PEP 622 is a Python Enhancement Proposal that introduced the design for structural pattern matching syntax later adopted in Python 3.10.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69b34542fd908190b11b08faad8decfd |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3512ec18481908a7b5c29b3902b53 |
completed | March 12, 2026, 11:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d094f5fc819083eddc234f46f6a1 |
completed | March 14, 2026, 9:18 p.m. |
| NEDg | Description generation | batch_69b5d10a20248190b3214509cb637ff4 |
completed | March 14, 2026, 9:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5d4f08ac4819097e71276be11403d |
completed | March 14, 2026, 9:36 p.m. |
Created at: March 12, 2026, 11:13 p.m.