Triple
T30575962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Slater as Daniel Molloy |
E778244
|
entity |
| Predicate | sharesScenesWith |
P89587
|
FINISHED |
| Object | Brad Pitt as Louis de Pointe du Lac |
—
|
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: Brad Pitt as Louis de Pointe du Lac | Statement: [Christian Slater as Daniel Molloy, sharesScenesWith, Brad Pitt as Louis de Pointe du Lac]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesScenesWith Context triple: [Christian Slater as Daniel Molloy, sharesScenesWith, Brad Pitt as Louis de Pointe du Lac]
-
A.
sharedSceneWith
chosen
Indicates that two entities appear together within the same scene or setting.
-
B.
sharesStageWith
Indicates that two or more performers appear or perform together on the same stage during a shared event or production.
-
C.
sharesActorWith
Indicates that two entities are associated with at least one of the same actors (e.g., performers or participants) in common.
-
D.
sharesAreaWith
Indicates that two entities occupy or overlap the same geographic or spatial area.
-
E.
sharesWith
Indicates that one entity gives another entity access to or use of something it possesses.
- 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_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fe7b1c506c8190869c1a22031e0571 |
completed | May 9, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69fe796b2bdc8190a86980d44008f875 |
completed | May 9, 2026, 12:01 a.m. |
Created at: April 29, 2026, 8:22 p.m.