Triple
T35621636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Four Girls in Town |
E1029326
|
entity |
| Predicate | hasCastOfCharacters |
P89780
|
FINISHED |
| Object | four young women competing for a film role |
—
|
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: four young women competing for a film role | Statement: [Four Girls in Town, hasCastOfCharacters, four young women competing for a film role]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCastOfCharacters Context triple: [Four Girls in Town, hasCastOfCharacters, four young women competing for a film role]
-
A.
hasCastCharacter
Indicates that a media work includes a specific character as part of its cast.
-
B.
hasCast
chosen
Indicates that a creative work features a particular group of performers or actors.
-
C.
hasCastOrCrew
Indicates that an entity (such as a film or show) is associated with one or more people who are part of its cast or crew.
-
D.
hasHumanCast
Indicates that a work or production features human performers as part of its cast.
-
E.
hasMainCharacterFrom
Indicates that a work of fiction has a main character who originates from or belongs to a specified place, group, or source.
- 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_69f76e0709408190bbe322bf1707ef6b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff9b1ad27081908f8a492396950795 |
completed | May 9, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69ff9a6354c48190ae21070c1424cb7a |
completed | May 9, 2026, 8:34 p.m. |
Created at: May 3, 2026, 4:05 p.m.