Triple
T2313132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PEP |
E51003
|
entity |
| Predicate | introducedBy |
P513
|
FINISHED |
| Object | Barry Warsaw |
E259571
|
NE 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: Barry Warsaw | Statement: [PEP, introducedBy, Barry Warsaw]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barry Warsaw Context triple: [PEP, introducedBy, Barry Warsaw]
-
A.
Barry Warsaw
chosen
Barry Warsaw is a prominent Python developer and core contributor known for his significant role in the evolution of the Python language and its community.
-
B.
Joel Podolny
Joel Podolny is an American sociologist and academic leader known for his work on organizational behavior and for serving in senior roles at top universities and major companies, including as a dean and corporate executive.
-
C.
Mike Sokolsky
Mike Sokolsky is a co-founder of the online education platform Udacity, known for its technology-focused courses and nanodegree programs.
-
D.
Martin Jurow
Martin Jurow was an American film producer best known for his work on classic mid-20th-century Hollywood movies, including the iconic Audrey Hepburn film "Breakfast at Tiffany's."
-
E.
Andrew Rabinovich
Andrew Rabinovich is a computer scientist and researcher known for his contributions to computer vision and deep learning, including influential work at Google.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc61c1ef08190911d5f58c2e91189 |
completed | March 7, 2026, 6:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aeb3bbea88819089f069be4d369692 |
completed | March 9, 2026, 11:49 a.m. |
Created at: March 4, 2026, 7:49 p.m.