Triple
T30047318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shavertown, New York |
E763489
|
entity |
| Predicate | regionTypeBeforeSubmergence |
P138122
|
FINISHED |
| Object | agricultural area |
—
|
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: agricultural area | Statement: [Shavertown, New York, regionTypeBeforeSubmergence, agricultural area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionTypeBeforeSubmergence Context triple: [Shavertown, New York, regionTypeBeforeSubmergence, agricultural area]
-
A.
preSubmergenceLandscape
chosen
Indicates the landscape configuration or conditions that existed before an area was submerged under water.
-
B.
notableNearbyFeatureBeforeSubmergence
Indicates that a location had a particular notable nearby feature prior to being submerged or flooded.
-
C.
hasCauseOfSubmergence
Indicates a relationship where one entity is the cause or reason for another entity becoming submerged or underwater.
-
D.
preSubmergenceElevation
Indicates the elevation or height of something before it becomes submerged or covered by water.
-
E.
landsPreviouslyBelongedTo
Indicates that the specified lands were owned, controlled, or possessed by a different party at an earlier time.
- 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_69fdd07a34c08190982b8c61c2775cf6 |
completed | May 8, 2026, noon |
| PD | Predicate disambiguation | batch_69fdbd25c7908190b72fca8de7ce503f |
completed | May 8, 2026, 10:38 a.m. |
Created at: April 29, 2026, 6:54 p.m.