Triple
T34443993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hot Pursuit |
E884167
|
entity |
| Predicate | hasSofiaVergaraAs |
P160083
|
FINISHED |
| Object | lead actress |
—
|
LITERAL 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: lead actress | Statement: [Hot Pursuit, hasSofiaVergaraAs, lead actress]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSofiaVergaraAs Context triple: [Hot Pursuit, hasSofiaVergaraAs, lead actress]
-
A.
hasGloria
Indicates that an entity possesses, includes, or is associated with Gloria in some specified way.
-
B.
hasAssociatedActress
chosen
Indicates that an entity is linked to an actress who is associated with it in a relevant context (e.g., participation, representation, or involvement).
-
C.
hasKhloeRole
Indicates that an entity holds or is assigned the specific role identified as "Khloe" in relation to another entity or context.
-
D.
hasHumanCast
Indicates that a work or production features human performers as part of its cast.
-
E.
hasBondGirl
Indicates that a person, typically a James Bond character, is associated with a romantic or significant female partner known as a "Bond girl."
- F. None of above.
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_69f349c548d88190978e2a82502c03d0 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd49f6dbac81909744373a357b7982 |
completed | May 8, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69fd48ed68f481908374183c66a6b055 |
completed | May 8, 2026, 2:22 a.m. |
Created at: May 1, 2026, 2 a.m.