Triple
T13668082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sam Tyler |
E327673
|
entity |
| Predicate | policeRankIn1973 |
P47215
|
FINISHED |
| Object | Detective Inspector |
—
|
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 Inspector | Statement: [Sam Tyler, policeRankIn1973, Detective Inspector]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policeRankIn1973 Context triple: [Sam Tyler, policeRankIn1973, Detective Inspector]
-
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.
civilServiceRank
Indicates that one entity holds a specific rank or position within a civil service hierarchy relative to another entity or classification.
-
D.
commissionedOfficerRank
Indicates that one entity holds a rank that qualifies them as a commissioned officer in a formal organizational hierarchy.
-
E.
isHighestRankedUniformedOfficerIn
Indicates that one entity holds the top-ranking position among all uniformed officers within a specified organization or jurisdiction.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65832688190aea688fee0a7cbdb |
completed | April 12, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8d8d0881908d6e89954f44eed4 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:52 p.m.