Triple
T22314723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NYPD Deputy Chief |
E551611
|
entity |
| Predicate | hasRankCodeType |
P56964
|
FINISHED |
| Object | civil service / discretionary executive appointment |
—
|
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: civil service / discretionary executive appointment | Statement: [NYPD Deputy Chief, hasRankCodeType, civil service / discretionary executive appointment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRankCodeType Context triple: [NYPD Deputy Chief, hasRankCodeType, civil service / discretionary executive appointment]
-
A.
hasRankCategory
Indicates that an entity is assigned to a particular rank-based classification or level within an ordered hierarchy.
-
B.
hasTypeCode
chosen
Indicates that an entity is associated with a specific type classification represented by a code.
-
C.
rankCode
Indicates the specific rank or hierarchical level assigned to an entity, typically encoded as a standardized code.
-
D.
containsRank
Indicates that one entity includes or encompasses another entity that has a specific rank or hierarchical level within it.
-
E.
hasRankContext
Indicates that an entity’s rank or ordering is defined, interpreted, or constrained within a specific contextual framework or situation.
- 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_69e11e4776588190abb21e5cea79973f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15751bf208190b8938a00d1afd157 |
completed | April 29, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69e73004d9e88190bb862319a5aea06b |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:42 p.m.