Triple
T26281105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manapparai |
E660699
|
entity |
| Predicate | distanceToTiruchirappalli |
P194844
|
FINISHED |
| Object | approximately 40 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 40 kilometres | Statement: [Manapparai, distanceToTiruchirappalli, approximately 40 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTiruchirappalli Context triple: [Manapparai, distanceToTiruchirappalli, approximately 40 kilometres]
-
A.
distanceFrom Tiruchirappalli
chosen
Indicates the measured spatial distance between an entity and the location Tiruchirappalli.
-
B.
distanceFromTirupati
Indicates the measured distance between a given location and Tirupati.
-
C.
distanceFromChennai
Indicates the spatial distance between a given entity or location and the city of Chennai.
-
D.
distanceFromChittoor
Indicates the spatial distance between a given location and the reference location Chittoor.
-
E.
distanceToKanyakumari
Indicates the spatial distance between a given location and Kanyakumari.
- 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_69ee812960d081909cff6085cc9fa3a6 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69fddac4e2f48190a9301d3422658b29 |
completed | May 8, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69fdda06969c8190b5d033964ea2a690 |
completed | May 8, 2026, 12:41 p.m. |
Created at: April 26, 2026, 10 p.m.