Triple
T18826731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nawalapitiya |
E460405
|
entity |
| Predicate | distanceFromKandy |
P110553
|
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: [Nawalapitiya, distanceFromKandy, approximately 40 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromKandy Context triple: [Nawalapitiya, distanceFromKandy, approximately 40 kilometres]
-
A.
distanceToKandy_km
chosen
Indicates the physical distance, measured in kilometers, from a given location to Kandy.
-
B.
distanceFromGalle_km
Indicates the physical distance, measured in kilometers, between an entity and the location Galle.
-
C.
distanceToBatticaloa_km
Indicates the physical distance, measured in kilometers, between an entity’s location and Batticaloa.
-
D.
distanceFromKotaBharu
Indicates the spatial distance between an entity’s location and the city of Kota Bharu.
-
E.
distanceToKota
Indicates the measured distance between a given entity and the location referred to as Kota.
- 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a6bec7b08190b040ec8b3693f037 |
completed | April 20, 2026, 4:08 a.m. |
| PD | Predicate disambiguation | batch_69e48d1b10ec8190985c6fb5766ff981 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:56 a.m.