Triple
T26783138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rangapara |
E670303
|
entity |
| Predicate | distanceToTezpurApproxKm |
P198074
|
FINISHED |
| Object | about 35 kilometres |
—
|
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 35 kilometres | Statement: [Rangapara, distanceToTezpurApproxKm, about 35 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTezpurApproxKm Context triple: [Rangapara, distanceToTezpurApproxKm, about 35 kilometres]
-
A.
distanceFromGuwahati_km
Indicates the physical distance, measured in kilometers, between an entity and the location of Guwahati.
-
B.
distanceToSiliguri_km
Indicates the physical distance, measured in kilometers, between a given location and Siliguri.
-
C.
distanceFromShillong
Indicates the spatial distance between a given entity or location and Shillong.
-
D.
distanceToGangtok
Indicates the measured spatial distance between a given location or entity and the city of Gangtok.
-
E.
distanceToJamshedpur_km
Indicates the physical distance, measured in kilometers, between a given location and Jamshedpur.
- 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69fec8aef1d8819094c7fd7074038e6b |
completed | May 9, 2026, 5:39 a.m. |
| PD | Predicate disambiguation | batch_69fec639876481908efd84a3631a4271 |
completed | May 9, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69fec8adaa308190a9a276f8c36f15f0 |
completed | May 9, 2026, 5:39 a.m. |
Created at: April 27, 2026, 4:10 a.m.