Triple
T21990674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lou Taylor Pucci |
E543077
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Lou |
—
|
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: Lou | Statement: [Lou Taylor Pucci, givenName, Lou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lou Context triple: [Lou Taylor Pucci, givenName, Lou]
-
A.
Lou
chosen
Lou is a common diminutive form of the given name Louise.
-
B.
Lou
Lou is a recurring Springfield police officer on the animated television series "The Simpsons," known as Chief Wiggum’s level-headed, deadpan partner.
-
C.
Lou
Lou is a central character in the Canadian romantic drama film "Take This Waltz," which explores themes of love, fidelity, and emotional restlessness.
-
D.
Lou
Lou is a character in the television miniseries "The Continental: From the World of John Wick," set in the action-packed criminal underworld of the John Wick franchise.
-
E.
Lou
Lou is a skilled and resourceful partner-in-crime who helps mastermind the heist in the film "Ocean's 8."
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1270d7cbc819086eea86be04a2ec0 |
completed | April 28, 2026, 9:30 p.m. |
Created at: April 16, 2026, 8:05 p.m.