Triple
T149450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Army Cadet Force |
E3399
|
entity |
| Predicate | hasAdultRank |
P6059
|
FINISHED |
| Object | Sergeant Instructor |
—
|
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: Sergeant Instructor | Statement: [Army Cadet Force, hasAdultRank, Sergeant Instructor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdultRank Context triple: [Army Cadet Force, hasAdultRank, Sergeant Instructor]
-
A.
mpaaRating
Indicates the official Motion Picture Association of America (MPAA) content rating assigned to a film or audiovisual work.
-
B.
bbfcRatingUK
Indicates the film or media content rating assigned by the British Board of Film Classification (BBFC) in the United Kingdom.
-
C.
TVShare
Indicates a relationship where one entity shares access to or usage of a television (or TV-related content/service) with another entity.
-
D.
TVRating
Indicates the content rating assigned to a television program, reflecting its suitability for specific audiences.
-
E.
hasAge
Indicates that an entity possesses a specific age value, typically expressed as a number of time units since its birth or creation.
- F. None of above. chosen
Provenance (4 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a2580ca15481909fa3e87d804a1b23 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a256599db08190a7b000b381d32ec4 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a25737f9188190b9690dce98aed83a |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.