Triple
T33858564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LaOtto, Indiana |
E867856
|
entity |
| Predicate | proximityToRegionalCenter |
P55639
|
FINISHED |
| Object | close to Fort Wayne metropolitan 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: close to Fort Wayne metropolitan area | Statement: [LaOtto, Indiana, proximityToRegionalCenter, close to Fort Wayne metropolitan area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proximityToRegionalCenter Context triple: [LaOtto, Indiana, proximityToRegionalCenter, close to Fort Wayne metropolitan area]
-
A.
hasRegionalCenterNearby
Indicates that a regional center is located in close proximity to the referenced entity.
-
B.
featuresRegionalProximity
chosen
Indicates that one entity is located near or in close geographic proximity to a particular region or another entity.
-
C.
administrativeCenterDistance
Indicates the distance between an entity and the administrative center that governs or represents it.
-
D.
distanceFromRegionalCapital
Indicates the measured spatial distance between a given place and its corresponding regional capital.
-
E.
isNearCapitalCity
Indicates that an entity is located close to, or in the immediate vicinity of, a capital city.
- 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_69f349943ccc8190a3c41a3e0ae46cbf |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7007970ac819092f5ab972587afd3 |
completed | May 3, 2026, 7:59 a.m. |
| PD | Predicate disambiguation | batch_69f6fc59518081908b0275f47721d561 |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:47 a.m.