Triple
T17817124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Christie |
E444873
|
entity |
| Predicate | githubUsername |
P3930
|
FINISHED |
| Object | tomchristie |
—
|
NE NERFINISHED |
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: tomchristie | Statement: [Tom Christie, githubUsername, tomchristie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: tomchristie Context triple: [Tom Christie, githubUsername, tomchristie]
-
A.
James Christie
James Christie was an 18th-century British auctioneer who founded the renowned auction house Christie's in London.
-
B.
Tom Christie
chosen
Tom Christie is a software developer best known for creating the Starlette ASGI framework and the Django REST framework in the Python ecosystem.
-
C.
Andrew Hoy
Andrew Hoy is a renowned Australian equestrian and multiple Olympic medalist, celebrated as one of the country’s most successful eventing riders.
-
D.
David Weir
David Weir is a British Paralympic wheelchair racer and multiple gold medalist renowned for his achievements on the track and in major marathons.
-
E.
Ed Christie
Ed Christie is an American puppet designer and builder best known for his long-time work with Jim Henson’s Muppets and Sesame Street characters.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9f0de78819099395b14db75a8a6 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48880457c81908214741d6cd7a1ee |
completed | April 19, 2026, 7:47 a.m. |
Created at: April 10, 2026, 10:14 a.m.