Triple
T10751996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renée Zellweger |
E253592
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Judy |
E287281
|
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: Judy | Statement: [Renée Zellweger, notableWork, Judy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Judy Context triple: [Renée Zellweger, notableWork, Judy]
-
A.
Judy
Judy is a central teenage character in the film "Rebel Without a Cause," known for her complex relationship with her parents and her emotional bond with Jim Stark.
-
B.
Judy
chosen
"Judy" is a 2019 biographical drama film in which Renée Zellweger portrays legendary entertainer Judy Garland during her final years, a role that earned her widespread acclaim and major acting awards.
-
C.
Judy
Judy is a character in the 2014 British apocalyptic comedy film "The Second Coming."
-
D.
Judy
Judy was the Allied reporting name for the Japanese Yokosuka D4Y carrier-based dive bomber used by the Imperial Japanese Navy during World War II.
-
E.
Judy
Judy is the familiar nickname of Judy Agnew, who was the Second Lady of the United States during Spiro Agnew’s vice presidency.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d71dc184d0819085f8bc4edb034377 |
completed | April 9, 2026, 3:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e1548affbc8190bbca099f8c8d4910 |
completed | April 16, 2026, 9:28 p.m. |
Created at: April 8, 2026, 9:15 p.m.