Triple
T11262725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Isle County, Vermont |
E266604
|
entity |
| Predicate | isSmallCountyByPopulation |
P98800
|
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: [Grand Isle County, Vermont, isSmallCountyByPopulation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSmallCountyByPopulation Context triple: [Grand Isle County, Vermont, isSmallCountyByPopulation, true]
-
A.
isSmallDistrict
Indicates that a district is classified as small, typically based on its limited size, population, or administrative scope.
-
B.
isSmallAreaMunicipality
Indicates that a municipality is classified as a small-area municipality, typically based on limited geographic size or population.
-
C.
isSmallCity
Indicates that a city has a relatively small population size or limited geographic/urban extent compared to typical cities.
-
D.
hasVerySmallResidentPopulation
Indicates that the subject location has a resident population that is extremely small in size.
-
E.
isOneOfMostPopulousCountiesIn
Indicates that a county ranks among the counties with the highest population within a specified larger region or jurisdiction.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e94c066c8190be1e032eb328e5fe |
completed | April 9, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69d7879bc56c8190b2e8d2193f29de05 |
completed | April 9, 2026, 11:03 a.m. |
| PDg | Predicate description generation | batch_69d796cf74308190a5b29d0dd82954a2 |
completed | April 9, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:31 p.m.