Triple
T7515962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barichara |
E177643
|
entity |
| Predicate | distanceToDepartmentCapital |
P77414
|
FINISHED |
| Object | approximately 120 km |
—
|
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: approximately 120 km | Statement: [Barichara, distanceToDepartmentCapital, approximately 120 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToDepartmentCapital Context triple: [Barichara, distanceToDepartmentCapital, approximately 120 km]
-
A.
distanceFromCapital
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
B.
districtHeadquartersDistance
Indicates the distance between a place and its corresponding district headquarters.
-
C.
prefectureCapitalDistance
Indicates the distance between a prefecture and its designated capital city.
-
D.
hasCountyCapitalDistance
Indicates a distance relationship specifying how far a county is from its capital.
-
E.
capitalOfDepartment
Indicates that a city or town serves as the administrative capital of a specified department (an administrative division).
- 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_69c69f2891148190a484f3b8222c6f1b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5f595148190b36649b0095bb898 |
completed | March 27, 2026, 9:26 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d44e9481909813e073b194f6f4 |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f574d8a8819095749518dad13791 |
completed | March 27, 2026, 9:24 p.m. |
Created at: March 27, 2026, 3:45 p.m.