Triple
T25048966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Ancram, New York |
E627322
|
entity |
| Predicate | hasHistoricSettlementPattern |
P126028
|
FINISHED |
| Object | hamlets |
—
|
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: hamlets | Statement: [Town of Ancram, New York, hasHistoricSettlementPattern, hamlets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricSettlementPattern Context triple: [Town of Ancram, New York, hasHistoricSettlementPattern, hamlets]
-
A.
hasSettlementHistory
Indicates that an entity has a documented history of human settlement or habitation in relation to another entity (such as a place or time period).
-
B.
historicalPattern
chosen
Indicates a recurring relationship or sequence of events between entities that has been observed over time.
-
C.
hasHistoricGround
Indicates that one entity is located on, associated with, or includes land or grounds of historical significance related to another entity.
-
D.
hasSettlementContinuitySince
Indicates that a settlement has existed continuously at a location since a specified point in time.
-
E.
hasHistoricBasisIn
Indicates that something is grounded in, derived from, or justified by historical events, practices, or precedents.
- 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.