Triple
T38420131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chippawa, Ontario |
E903204
|
entity |
| Predicate | nearUSState |
P180772
|
FINISHED |
| Object | New York |
—
|
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 | Statement: [Chippawa, Ontario, nearUSState, New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearUSState Context triple: [Chippawa, Ontario, nearUSState, New York]
-
A.
nearbyState
Indicates that one state is geographically adjacent to or in close proximity to another state.
-
B.
nearbyStateOrProvince
chosen
Indicates that one state or province is geographically close to, but not necessarily directly bordering, another state or province.
-
C.
nearestStateOrTerritory
Indicates that one location is the closest state or territory to another location, typically in terms of geographic distance.
-
D.
nearByCityState
Indicates that a city is geographically close to or within the same general area as a specified state.
-
E.
nearestMajorState
Indicates the relationship where a given location is associated with the closest major state to it, typically by geographic distance.
- 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_69f76e67e4fc8190a7d08dfe9a8af998 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd1499e2c81909bafd84dc4810f45 |
completed | May 7, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69fcccf024ec819086383ffbb6cfc036 |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:31 p.m.