Triple
T10851810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Python 3.8 |
E256163
|
entity |
| Predicate | introducesSyntax |
P38052
|
FINISHED |
| Object | := |
—
|
LITERAL FINISHED |
How this triple was built (2 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: := | Statement: [Python 3.8, introducesSyntax, :=]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducesSyntax Context triple: [Python 3.8, introducesSyntax, :=]
-
A.
definesSyntax
chosen
Indicates that one entity specifies or determines the formal structure, rules, or grammar by which another entity is expressed or interpreted.
-
B.
hasIntroduction
Indicates that one entity includes or provides an introductory section, part, or presentation for another entity.
-
C.
sectionIntroduced
Indicates that a particular section was introduced or added at a specific point in time or context.
-
D.
introduced
Indicates that one entity caused another entity to become known, presented, or brought into use for the first time to a person, group, or context.
-
E.
introducedLanguageElements
Indicates that an entity (such as a person, organization, or document) brought certain language elements (e.g., words, constructs, or features) into use or made them known for the first time.
- F. None of above.
Provenance (3 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75117b76c8190b0fb216b1428c3c7 |
completed | April 9, 2026, 7:11 a.m. |
| PD | Predicate disambiguation | batch_69d70d2b51448190bae748ed6c23edde |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.