Triple
T26329343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Syracuse Police Department |
E662337
|
entity |
| Predicate | hasSwornType |
P160252
|
FINISHED |
| Object | police officer |
—
|
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: police officer | Statement: [Syracuse Police Department, hasSwornType, police officer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSwornType Context triple: [Syracuse Police Department, hasSwornType, police officer]
-
A.
hasSwornStatus
Indicates that an entity is formally bound by an oath or sworn commitment, reflecting an official or pledged status in relation to another entity or role.
-
B.
hasOathTo
Indicates a relationship in which one entity is bound by an oath or sworn commitment to another entity.
-
C.
oathSwornBefore
Indicates that an oath or solemn promise has been formally declared in the presence of a specified person, group, or authority.
-
D.
swornInOn
Indicates that an individual formally assumes an office, role, or duty by taking an official oath on a specified date, occasion, or object.
-
E.
mayBeAffirmedRatherThanSworn
Indicates that a statement or testimony can be confirmed by affirmation instead of being given under a formal oath.
- F. None of above. chosen
Provenance (4 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_69ee812f32748190871d970c4e2a8ddf |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f60f67cde08190b9bfe877342778eb |
completed | May 2, 2026, 2:51 p.m. |
| PD | Predicate disambiguation | batch_69f5f7ff548c8190a23e98c5e66e0bc7 |
completed | May 2, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69f5ffc6268c8190b63f6360ebadab73 |
completed | May 2, 2026, 1:44 p.m. |
Created at: April 26, 2026, 10:32 p.m.