Triple
T14491717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevadia |
E359376
|
entity |
| Predicate | distanceToVadodara |
P114440
|
FINISHED |
| Object | approximately 90 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: approximately 90 kilometres | Statement: [Kevadia, distanceToVadodara, approximately 90 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToVadodara Context triple: [Kevadia, distanceToVadodara, approximately 90 kilometres]
-
A.
distanceToAhmedabad
Indicates the spatial distance between a given location or entity and the city of Ahmedabad.
-
B.
distanceFromBhavnagar
Indicates the spatial distance between a given entity or location and Bhavnagar.
-
C.
distanceToWardha
Indicates the spatial distance between a given entity and the location named Wardha.
-
D.
distanceFromBhopal
Indicates the measured spatial distance between a given location or entity and the city of Bhopal.
-
E.
distanceToJodhpur
Indicates the spatial distance between a given entity or location and the city of Jodhpur.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de930d820481908b9813014dd02540 |
completed | April 14, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69de5c4ccba08190a988bfda0bc9f5cb |
completed | April 14, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:20 a.m.