Triple
T410031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Supreme Court |
E9467
|
entity |
| Predicate | hasPresenceIn |
P2284
|
FINISHED |
| Object | each county of New York State |
—
|
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: each county of New York State | Statement: [New York Supreme Court, hasPresenceIn, each county of New York State]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPresenceIn Context triple: [New York Supreme Court, hasPresenceIn, each county of New York State]
-
A.
fieldPresenceIn
chosen
Indicates that something exists or is located within a particular field, area, or domain.
-
B.
hasRepresentationIn
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
-
C.
existsFor
Indicates that something is present, available, or holds true for a particular entity, context, or condition.
-
D.
hasPar
Indicates a relationship where one entity has another entity as its parent.
-
E.
hasCollection
Indicates that an entity possesses, maintains, or is associated with a set or group of related items treated as a collection.
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ed31681c8190ac32334562fb17fd |
completed | Feb. 28, 2026, 1:27 p.m. |
| PD | Predicate disambiguation | batch_69a2e9737694819080fde9adcc1aa4d4 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.