Triple
T30885815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Adventure of the Six Napoleons |
E786758
|
entity |
| Predicate | hasPoliceInspector |
P31758
|
FINISHED |
| Object | Inspector Lestrade |
—
|
NE NERFINISHED |
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: Inspector Lestrade | Statement: [The Adventure of the Six Napoleons, hasPoliceInspector, Inspector Lestrade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoliceInspector Context triple: [The Adventure of the Six Napoleons, hasPoliceInspector, Inspector Lestrade]
-
A.
hasPoliceRole
Indicates that an entity holds or performs a specific role, duty, or function within a police or law enforcement context.
-
B.
hasPolicePartner
Indicates that one entity has another entity as its partner in a police or law-enforcement context.
-
C.
hasPoliceChief
Indicates that an entity has, is associated with, or is under the authority of a specific police chief.
-
D.
hasPoliceInstitution
Indicates that an entity is associated with, governed by, or served by a particular police institution or law enforcement body.
-
E.
policeCharacter
chosen
Indicates that one entity serves as a police officer or law-enforcement figure in relation to another entity.
- 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_69f224bbfa7c81908448e0c261c523e3 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe031bc6208190860099aef72d8dcb |
completed | May 8, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69fe014c8b388190b5d4e0cb95ee2be5 |
completed | May 8, 2026, 3:29 p.m. |
Created at: April 29, 2026, 8:49 p.m.