Triple
T1429589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adobe Illustrator |
E30413
|
entity |
| Predicate | supportsFormat |
P203
|
FINISHED |
| Object |
AI
AI is Adobe Illustrator’s native vector graphics file format used to store and exchange editable artwork.
|
E163316
|
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: AI | Statement: [Adobe Illustrator, supportsFormat, AI]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AI Context triple: [Adobe Illustrator, supportsFormat, AI]
-
A.
AI
Amnesty International is a global non-governmental organization focused on protecting human rights and campaigning against abuses such as torture, unjust imprisonment, and the death penalty.
-
B.
Ai
Ai is a Chinese surname historically associated with the Jewish community of Kaifeng, reflecting their integration into broader Chinese society.
-
C.
xAI
xAI is an artificial intelligence company focused on developing advanced AI systems, founded and led by entrepreneur Elon Musk.
-
D.
ML
ML is a statically typed functional programming language developed at the University of Edinburgh, known for pioneering features like type inference, pattern matching, and modules that strongly influenced later languages such as Elm, Haskell, and OCaml.
-
E.
ML
ML is the postcode area in central Scotland that covers Motherwell and surrounding towns.
- 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: AI Triple: [Adobe Illustrator, supportsFormat, AI]
Generated description
AI is Adobe Illustrator’s native vector graphics file format used to store and exchange editable artwork.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: AI Target entity description: AI is Adobe Illustrator’s native vector graphics file format used to store and exchange editable artwork.
-
A.
AI
Amnesty International is a global non-governmental organization focused on protecting human rights and campaigning against abuses such as torture, unjust imprisonment, and the death penalty.
-
B.
Ai
Ai is a Chinese surname historically associated with the Jewish community of Kaifeng, reflecting their integration into broader Chinese society.
-
C.
xAI
xAI is an artificial intelligence company focused on developing advanced AI systems, founded and led by entrepreneur Elon Musk.
-
D.
ML
ML is a statically typed functional programming language developed at the University of Edinburgh, known for pioneering features like type inference, pattern matching, and modules that strongly influenced later languages such as Elm, Haskell, and OCaml.
-
E.
ML
ML is the postcode area in central Scotland that covers Motherwell and surrounding towns.
- 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_69a498fc69ec8190b61722bd4b67c4d2 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c4db2d7481908d241593d0e17d83 |
completed | March 1, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad016930ec8190ab3900d6f40c4aa0 |
completed | March 8, 2026, 4:56 a.m. |
| NEDg | Description generation | batch_69ad01d1c01c81908917c4837ed2b393 |
completed | March 8, 2026, 4:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad0265f610819085a2dd293abd4812 |
completed | March 8, 2026, 5 a.m. |
Created at: March 1, 2026, 8 p.m.