Triple
T28744322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jagiroad |
E731324
|
entity |
| Predicate | stateCapitalDistance_km |
P10889
|
FINISHED |
| Object | about 55 from Dispur |
—
|
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: about 55 from Dispur | Statement: [Jagiroad, stateCapitalDistance_km, about 55 from Dispur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stateCapitalDistance_km Context triple: [Jagiroad, stateCapitalDistance_km, about 55 from Dispur]
-
A.
distanceFromCapital
chosen
Indicates the measured distance between a given location and the capital city of its corresponding region or country.
-
B.
stateCapitalProximity
Indicates the spatial closeness or distance between a state’s capital city and another specified location.
-
C.
regionCapitalDistanceRelation
Indicates a relationship specifying the distance between a region and its capital.
-
D.
prefecturalCapitalDistanceRelation
Indicates a spatial relationship specifying the distance between an entity and the capital city of its prefecture.
-
E.
departmentCapitalDistanceKm
Indicates the distance in kilometers between a department and its capital.
- 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_69f043ecb5c081909ec9da1172d68ece |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: April 28, 2026, 6:04 a.m.