Triple
T35654667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Constabulary |
E1030250
|
entity |
| Predicate | hadSpecialistUnit |
P1198
|
FINISHED |
| Object | mountain rescue liaison |
—
|
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: mountain rescue liaison | Statement: [Northern Constabulary, hadSpecialistUnit, mountain rescue liaison]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadSpecialistUnit Context triple: [Northern Constabulary, hadSpecialistUnit, mountain rescue liaison]
-
A.
hasSpecialUnit
chosen
Indicates that an entity possesses or is associated with a distinct, designated unit that has a special role, function, or status.
-
B.
hasSpecialist
Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for it.
-
C.
hasSpecialistStatus
Indicates that an entity holds a recognized specialist designation or status in a particular field, role, or context.
-
D.
hasSpecialty
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
E.
hasMilitarySpeciality
Indicates that an entity possesses a specific military role, skill set, or area of professional expertise within the armed forces.
- 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_69f76e0938088190a8f199631e97dec3 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79f769dec81908e0e638851ac83dd |
completed | May 3, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69f79e4d885881908a3612e2e75cf84f |
completed | May 3, 2026, 7:13 p.m. |
Created at: May 3, 2026, 4:05 p.m.