Triple
T21483232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mickey Liddell |
E530047
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Jackie |
—
|
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: Jackie | Statement: [Mickey Liddell, notableWork, Jackie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jackie Context triple: [Mickey Liddell, notableWork, Jackie]
-
A.
Jackie
chosen
Jackie is a biographical drama film in which Natalie Portman portrays Jacqueline Kennedy in the aftermath of President John F. Kennedy’s assassination.
-
B.
Jackie
Jackie is the central protagonist of the film "Love Lies Bleeding," around whom the movie’s intense, character-driven narrative revolves.
-
C.
Jackie
"Jackie" is an album, likely in the pop or R&B genre, best known for featuring the song "I Bet."
-
D.
Jackie
"Jackie" is a stage play by Elfriede Jelinek that portrays the life and public image of Jacqueline Kennedy Onassis, in which actress Blair Brown delivered a notable performance.
-
E.
Jackie
Jackie is the central protagonist of the 2014 film "Ride," around whom the story’s emotional and narrative developments revolve.
- 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_69e0c45acc3881908e38d3f28964152b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea35945481909e5982429962de39 |
completed | April 23, 2026, 9:45 a.m. |
Created at: April 16, 2026, 6:21 p.m.