Triple
T9031378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chitrakoot division |
E216379
|
entity |
| Predicate | lawAndOrderRole |
P41321
|
FINISHED |
| Object | coordination of policing across districts |
—
|
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: coordination of policing across districts | Statement: [Chitrakoot division, lawAndOrderRole, coordination of policing across districts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lawAndOrderRole Context triple: [Chitrakoot division, lawAndOrderRole, coordination of policing across districts]
-
A.
policeCharacter
Indicates that one entity serves as a police officer or law-enforcement figure in relation to another entity.
-
B.
legalCaseRole
Indicates the specific role or capacity an entity holds within a legal case, such as plaintiff, defendant, judge, or attorney.
-
C.
legalSystemRole
chosen
Indicates the specific function, capacity, or position an entity holds within a legal or judicial system.
-
D.
actorRole
Indicates that an entity participates in an event or action in a specific capacity or function (such as performer, initiator, or responsible party).
-
E.
courtRole
Indicates the specific capacity or position an entity holds within a court proceeding or judicial context.
- 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_69ca83d10b608190b2b2f8e0a7faaf14 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6a9f2c7481909b4a272183f20585 |
completed | April 1, 2026, 12:45 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee3597c81908919cf866ae95c24 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:08 p.m.