Triple
T25049025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamlet of Hopewell Junction, New York |
E627323
|
entity |
| Predicate | hasNearbyStateRoute |
P118122
|
FINISHED |
| Object | New York State Route 52 |
—
|
NE NERFINISHED |
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: New York State Route 52 | Statement: [Hamlet of Hopewell Junction, New York, hasNearbyStateRoute, New York State Route 52]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyStateRoute Context triple: [Hamlet of Hopewell Junction, New York, hasNearbyStateRoute, New York State Route 52]
-
A.
hasNearbyStateLine
Indicates that one location is situated close to the boundary line of a neighboring state.
-
B.
hasNearbyPoint
chosen
Indicates that one entity has at least one other point located within a specified proximity or distance from it.
-
C.
adjacentStateRoute
Indicates that one state route is directly next to or shares a boundary or junction with another state route.
-
D.
hasNearbyFunction
Indicates that one entity has another entity located close by that serves a related or supportive function.
-
E.
hasNearbyCrossingPoint
Indicates that one location has a crossing point (such as a bridge, crosswalk, or intersection) situated close to it.
- 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_69e2ff2b4c80819087c916b2b16241b9 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f650c70d7c819093d9a0f005f7c8d5 |
completed | May 2, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 18, 2026, 6:08 a.m.