Triple
T17946339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Salamanca, New York |
E448710
|
entity |
| Predicate | hasLandCharacteristic |
P12436
|
FINISHED |
| Object | hilly terrain |
—
|
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: hilly terrain | Statement: [Town of Salamanca, New York, hasLandCharacteristic, hilly terrain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandCharacteristic Context triple: [Town of Salamanca, New York, hasLandCharacteristic, hilly terrain]
-
A.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
B.
hasLandComponent
Indicates that something includes, consists of, or is associated with a land-based part or portion as one of its components.
-
C.
hasGeographyCharacteristic
chosen
Indicates that an entity possesses a specific geographical feature, property, or attribute.
-
D.
hasLandform
Indicates that one entity possesses, contains, or is characterized by a particular natural landform.
-
E.
hasLandStatus
Indicates that an entity possesses a particular legal or administrative status regarding land (such as ownership, tenure, protection, or use designation).
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4ad99df408190a8a4e3d21c03fe71 |
completed | April 19, 2026, 10:25 a.m. |
| PD | Predicate disambiguation | batch_69e3f8f2bd088190b1e22ad4d9cc8b13 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:21 a.m.