Triple
T9160997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vellore |
E219819
|
entity |
| Predicate | distanceToChennai_km |
P37294
|
FINISHED |
| Object | approximately 135 |
—
|
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 135 | Statement: [Vellore, distanceToChennai_km, approximately 135]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToChennai_km Context triple: [Vellore, distanceToChennai_km, approximately 135]
-
A.
distanceFromChennai
chosen
Indicates the spatial distance between a given entity or location and the city of Chennai.
-
B.
distanceFromBengaluru
Indicates the measured spatial distance between a given entity’s location and the city of Bengaluru.
-
C.
distanceToDelhiByRoad_km
Indicates the road travel distance, measured in kilometers, from a given place to Delhi.
-
D.
distanceFromBangalore
Indicates the spatial distance separating a given entity or location from Bangalore.
-
E.
distanceToDelhiApproxKm
Indicates the approximate distance, measured in kilometers, between a given entity’s location and Delhi.
- 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_69ca83e3633c81908688a9fa2306ba99 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaa2ac0508190b2f5c801c2c26d66 |
completed | April 1, 2026, 5:16 a.m. |
| PD | Predicate disambiguation | batch_69cc6605c6808190a30d92da006206ac |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:21 p.m.