Triple
T4140806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Coxsackie, New York |
E89266
|
entity |
| Predicate | hasSmallTownCharacter |
P54112
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Town of Coxsackie, New York, hasSmallTownCharacter, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSmallTownCharacter Context triple: [Town of Coxsackie, New York, hasSmallTownCharacter, true]
-
A.
hasSuburbanCharacter
Indicates that something possesses qualities or features typically associated with suburban areas, such as lower density, residential focus, and car-oriented development.
-
B.
hasTown
Indicates that one entity possesses, contains, or is associated with a town as part of its structure, jurisdiction, or composition.
-
C.
isSmallCity
Indicates that a city has a relatively small population size or limited geographic/urban extent compared to typical cities.
-
D.
hasSmallTownIndustry
Indicates that a small town possesses or supports a particular type of industry or industrial activity.
-
E.
hasTownship
Indicates that one administrative area or jurisdiction includes or is associated with a specific township.
- 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_69aed95785788190ae75bcf0cd1cafdf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af03a0f3408190adba7a8513bd3d12 |
completed | March 9, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69af018a54848190987f18c066c75068 |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af039fb19c8190b20e62a3b3ad25c1 |
completed | March 9, 2026, 5:30 p.m. |
Created at: March 9, 2026, 3:43 p.m.