Triple
T2972773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York state politics |
E80318
|
entity |
| Predicate | hasRegionalPowerCenter |
P32293
|
FINISHED |
| Object | Long Island politics |
—
|
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: Long Island politics | Statement: [New York state politics, hasRegionalPowerCenter, Long Island politics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegionalPowerCenter Context triple: [New York state politics, hasRegionalPowerCenter, Long Island politics]
-
A.
hasHeadquartersInRegion
Indicates that an organization’s main administrative or corporate headquarters is located within a specified geographic region.
-
B.
hasRegionStrongPresence
chosen
Indicates that an entity maintains a significant, influential, or concentrated presence within a specified region.
-
C.
hadRegionalCenter
Indicates that an entity possessed, operated, or was associated with a specific regional center serving a defined geographic area.
-
D.
hasResearchCentersIn
Indicates that an entity maintains or operates research centers located within a specified place or region.
-
E.
hasBaseOfOperations
Indicates that an entity uses a particular location as its primary place of operation or activity.
- 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_69ad8b14ffe881908ffed62f9595c867 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad998656948190ba79d7196d735f34 |
completed | March 8, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69ad96105a708190a9ec4838cbcb1207 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:58 p.m.