Triple
T12375776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bihar Sharif |
E295118
|
entity |
| Predicate | distanceFromNalandaRuins |
P104645
|
FINISHED |
| Object | approximately 15 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 15 km | Statement: [Bihar Sharif, distanceFromNalandaRuins, approximately 15 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromNalandaRuins Context triple: [Bihar Sharif, distanceFromNalandaRuins, approximately 15 km]
-
A.
distanceFromAgra
Indicates the spatial distance between a given entity or location and the city of Agra.
-
B.
distanceFromVaranasi
Indicates the measured or specified distance between a given entity or location and the city of Varanasi.
-
C.
distanceToAyodhya
Indicates the measured spatial distance between a given entity’s location and the location of Ayodhya.
-
D.
distanceToSomnath
Indicates the spatial distance between a given entity or location and Somnath.
-
E.
distanceFromKurukshetra
Indicates the spatial distance between a given entity and the location of Kurukshetra.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93fb8d6c081909e8bbbd52c73f29c |
completed | April 10, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69d93ed256788190b704cad171a4824e |
completed | April 10, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69d93fa244148190a960be3ff6f1cf45 |
completed | April 10, 2026, 6:21 p.m. |
Created at: April 8, 2026, 9:54 p.m.