Triple
T14922175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elba, New York (former name of the area) |
E371540
|
entity |
| Predicate | hasGeographicType |
P116678
|
FINISHED |
| Object | township |
—
|
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: township | Statement: [Elba, New York (former name of the area), hasGeographicType, township]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGeographicType Context triple: [Elba, New York (former name of the area), hasGeographicType, township]
-
A.
hasGeographyCharacteristic
Indicates that an entity possesses a specific geographical feature, property, or attribute.
-
B.
isGeographicalEntity
Indicates that something exists as a distinct geographic feature, area, or place within physical space.
-
C.
containsGeographicalArea
Indicates that one geographical area spatially encompasses or includes another geographical area within its boundaries.
-
D.
hasGeographicBasis
Indicates that something is grounded in, derived from, or defined by a particular geographic location or area.
-
E.
geographicContext
Indicates that one entity is situated within, associated with, or characterized by the geographic setting or region defined by another entity.
- F. None of above. chosen
Provenance (4 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_69d85cc7ea3481908228b5acb7d06f12 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded63121e48190b54eb2546acc3c93 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:34 a.m.