Triple
T30047282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arena, New York |
E763488
|
entity |
| Predicate | locatedNearFormerSettlement |
P98811
|
FINISHED |
| Object | Shavertown, 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: Shavertown, New York | Statement: [Arena, New York, locatedNearFormerSettlement, Shavertown, New York]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedNearFormerSettlement Context triple: [Arena, New York, locatedNearFormerSettlement, Shavertown, New York]
-
A.
locatedInOrNearModernSettlement
Indicates that something is situated within or in close proximity to a present-day town, city, or other populated settlement.
-
B.
locatedNearFormer
chosen
Indicates that one entity is situated close to another entity that previously occupied a nearby or the same location.
-
C.
historicallyLocatedNear
Indicates that, in a historical context, one entity was geographically situated close to another entity.
-
D.
locatedInFormerNamePlace
Indicates that an entity is located in a place that is referred to by its former or historical name rather than its current name.
-
E.
originOfSettlement
Indicates the place, source, or starting point from which a settlement was established or originated.
- 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_69f22470a89c8190be7273297c0e0d19 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a008e29f76881908e656dbbd7fceea3 |
completed | May 10, 2026, 1:54 p.m. |
| PD | Predicate disambiguation | batch_6a008dc01b308190bc26e69814692f82 |
completed | May 10, 2026, 1:53 p.m. |
Created at: April 29, 2026, 6:54 p.m.