Triple
T35859856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tayside Police |
E1036915
|
entity |
| Predicate | lastChiefConstable |
P148514
|
FINISHED |
| Object |
Justine Curran
Justine Curran is a British police officer who served as the final Chief Constable of Tayside Police before moving on to lead Humberside Police.
|
E2157918
|
NE FINISHED |
How this triple was built (3 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: Justine Curran | Statement: [Tayside Police, lastChiefConstable, Justine Curran]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Justine Curran Triple: [Tayside Police, lastChiefConstable, Justine Curran]
Generated description
Justine Curran is a British police officer who served as the final Chief Constable of Tayside Police before moving on to lead Humberside Police.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lastChiefConstable Context triple: [Tayside Police, lastChiefConstable, Justine Curran]
-
A.
previousChiefConstable
chosen
Indicates that one entity served as the chief constable of another entity at an earlier time, prior to the current chief constable.
-
B.
currentGardaCommissioner
Indicates that one entity holds the position of the current Garda Commissioner (the present head of the national police service of Ireland) for the other entity.
-
C.
chiefLieutenantOf
Indicates that one person serves as the primary subordinate or top-ranking assistant to another leader or authority figure.
-
D.
chiefOfSecurity
Indicates that one entity holds the primary responsibility for overseeing and managing the security operations of another entity.
-
E.
hasChiefFireOfficer
Indicates that an entity has, is associated with, or is overseen by a specific chief fire officer.
- F. None of above.
Provenance (6 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_69f76e1d279c8190843e5b64a0a12c3f |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aa3883d48190b05e3d2da7a017ae |
completed | May 3, 2026, 8:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a389c3510308190b8109f8e670e0642 |
completed | June 22, 2026, 2:21 a.m. |
| NEDg | Description generation | batch_6a389cfaa1fc81908e382b4befed99f6 |
completed | June 22, 2026, 2:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a389d9dcbd88190b86408dcb14f8128 |
completed | June 22, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f7a8d435288190b30b1991fb003121 |
completed | May 3, 2026, 7:58 p.m. |
Created at: May 3, 2026, 4:06 p.m.