Triple
T18261156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Assistant Chief Constable Freddie Fisher |
E437357
|
entity |
| Predicate | conflictGround |
P131074
|
FINISHED |
| Object | professional ethics |
—
|
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: professional ethics | Statement: [Assistant Chief Constable Freddie Fisher, conflictGround, professional ethics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conflictGround Context triple: [Assistant Chief Constable Freddie Fisher, conflictGround, professional ethics]
-
A.
conflictCountry
Indicates that there is an armed conflict or war involving the referenced country as a participant.
-
B.
conflictIn
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
C.
regionOfConflict
Indicates that a specified region is the location where a particular conflict or dispute takes place.
-
D.
conflictBelligerent
Indicates that an entity is a participating belligerent (e.g., a country, group, or force) in a specific conflict.
-
E.
conflictRegion
Indicates that the entities are located in or associated with a geographic area characterized by active or recent conflict, tension, or hostilities.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff7591b4819083f2b29d60298747 |
completed | April 19, 2026, 4:14 p.m. |
| PD | Predicate disambiguation | batch_69e44fcdee748190bae6fb76e0cb22f3 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:34 a.m.