Triple
T29446003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Danny "Danno" Williams |
E746846
|
entity |
| Predicate | policeRankInFiction |
P47215
|
FINISHED |
| Object | detective |
—
|
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: detective | Statement: [Danny "Danno" Williams, policeRankInFiction, detective]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policeRankInFiction Context triple: [Danny "Danno" Williams, policeRankInFiction, detective]
-
A.
policeRank
chosen
Indicates that one entity holds a specific rank or position within a police organization relative to another entity.
-
B.
policeRankStructure
Indicates the hierarchical ranking relationship that defines levels of authority and command within a police organization.
-
C.
policeCharacter
Indicates that one entity serves as a police officer or law-enforcement figure in relation to another entity.
-
D.
officersKnownAs
Indicates that certain officers are referred to or recognized by a particular name or designation.
-
E.
politicalAffiliationInFiction
Indicates a fictional character’s association or alignment with a political party, ideology, or movement within a narrative work.
- 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_69f0a7a230488190b44a97fe3d16f731 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d26ceb08819091c71c001e954936 |
completed | May 3, 2026, 4:43 a.m. |
Created at: April 28, 2026, 3:27 p.m.