Triple
T7522627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jalpaiguri |
E177808
|
entity |
| Predicate | distanceToSiliguri_km |
P77304
|
FINISHED |
| Object | about 45 |
—
|
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 45 | Statement: [Jalpaiguri, distanceToSiliguri_km, about 45]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToSiliguri_km Context triple: [Jalpaiguri, distanceToSiliguri_km, about 45]
-
A.
distanceFromGuwahati_km
Indicates the physical distance, measured in kilometers, between an entity and the location of Guwahati.
-
B.
distanceFromKolkata
Indicates the spatial distance between a given location and the city of Kolkata.
-
C.
distanceToSrinagar_km
Indicates the physical distance, measured in kilometers, between a given place or entity and the city of Srinagar.
-
D.
distanceFromShimla_km
Indicates the physical distance, measured in kilometers, between a given place and Shimla.
-
E.
distanceFromChandigarh_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Chandigarh.
- 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_69c69f29bf3081909a146aec7755f185 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f7c3c4c08190ad418978afcc98ec |
completed | March 27, 2026, 9:33 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d6bb808190bdd04499fd3bceb6 |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6f555455c81908850210bcad96ac2 |
completed | March 27, 2026, 9:23 p.m. |
Created at: March 27, 2026, 3:46 p.m.