Triple
T23263883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Girl |
E582090
|
entity |
| Predicate | hasNoGivenNameInFilm |
P134266
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Girl, hasNoGivenNameInFilm, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoGivenNameInFilm Context triple: [The Girl, hasNoGivenNameInFilm, true]
-
A.
givenNameInFilm
Indicates that a person is referred to by a particular given (first) name within the context of a specific film.
-
B.
hasStageNameInFilm
Indicates that an individual is credited or referred to by a particular stage name in a specific film.
-
C.
hasFilmNamedAfter
Indicates that one entity (typically a person, place, event, or work) serves as the inspiration or subject for a film that bears its name or is explicitly titled after it.
-
D.
hasNoFilmAdaptationAsCharacter
Indicates that the subject has not appeared as a character in any film adaptation.
-
E.
hasNoPersonalNameIn
chosen
Indicates that an entity lacks a specific personal name within a given context, language, or naming system.
- 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_69e246079f58819085eaa9c260906880 |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f194cb76c48190869915cd93b44fcc |
completed | April 29, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:11 p.m.