Triple
T984522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sid Luft |
E21248
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Joey Luft |
E39870
|
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: Joey Luft | Statement: [Sid Luft, child, Joey Luft]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Joey Luft Context triple: [Sid Luft, child, Joey Luft]
-
A.
Joey Luft
chosen
Joey Luft is an American television producer and occasional actor best known as the son of legendary entertainer Judy Garland and producer Sidney Luft.
-
B.
Joey Newman
Joey Newman is an American composer and conductor known for his work on television scores and themes, including contributions to major sports broadcasts.
-
C.
Jeremy Jacobs
Jeremy Jacobs is an American billionaire businessman and longtime owner of the NHL’s Boston Bruins, known for his influential role in professional hockey and sports venue management.
-
D.
Drew Bagnell
Drew Bagnell is a roboticist and machine learning researcher known for his work in autonomous systems and his role as a co-founder and chief scientist at Aurora Innovation.
-
E.
Joshua Michael Stern
Joshua Michael Stern is an American film director and screenwriter known for helming biographical and dramatic feature films.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4959fe48190a78bd811cbc888ab |
completed | March 1, 2026, 9:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac1ce3c6fc81909fbbf04eef1b997e |
completed | March 7, 2026, 12:41 p.m. |
Created at: March 1, 2026, 7:41 p.m.