Triple
T32177068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MS One |
E821880
|
entity |
| Predicate | hasStatusInFilm |
P25517
|
FINISHED |
| Object | experimental facility |
—
|
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: experimental facility | Statement: [MS One, hasStatusInFilm, experimental facility]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStatusInFilm Context triple: [MS One, hasStatusInFilm, experimental facility]
-
A.
hasOutcomeInFilm
Indicates that a particular event, action, or situation results in a specific outcome within the context of a film.
-
B.
hasStageNameInFilm
Indicates that an individual is credited or referred to by a particular stage name in a specific film.
-
C.
hasFilmVersionStatus
chosen
Indicates whether and how a work has been adapted into a film, specifying the status of that film version.
-
D.
hasTypeOfUseInFilm
Indicates that something is associated with a specific manner or category of use within the context of a film.
-
E.
engagementStatusAcrossFilm
Indicates the state or progression of an engagement (such as a relationship, commitment, or involvement) as it changes or is maintained throughout the duration of a film.
- 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_69f3490755288190aee11740a34862f9 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69feecf1bb248190ba30f0bb1d22ee08 |
completed | May 9, 2026, 8:14 a.m. |
| PD | Predicate disambiguation | batch_69feea5f27748190b223ee4e3ba5a678 |
completed | May 9, 2026, 8:03 a.m. |
Created at: May 1, 2026, 12:34 a.m.