Triple
T19628394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mawanella |
E471198
|
entity |
| Predicate | distanceToKandyByRoad_km |
P110553
|
FINISHED |
| Object | approximately 30 |
—
|
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 30 | Statement: [Mawanella, distanceToKandyByRoad_km, approximately 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToKandyByRoad_km Context triple: [Mawanella, distanceToKandyByRoad_km, approximately 30]
-
A.
distanceToKandy_km
chosen
Indicates the physical distance, measured in kilometers, from a given location to Kandy.
-
B.
distanceToThimphuByRoad
Indicates the road travel distance required to go from a given place to Thimphu.
-
C.
distanceFromGalle_km
Indicates the physical distance, measured in kilometers, between an entity and the location Galle.
-
D.
distanceFromKathmandu
Indicates the measured spatial distance between a given location or entity and the city of Kathmandu.
-
E.
distanceToThimphu
Indicates the measured spatial distance between a given entity’s location and the city of Thimphu.
- 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_69d8e511f28481909f4bc3ea9191e54a |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e641007e5881908da78e50aa36f340 |
completed | April 20, 2026, 3:06 p.m. |
| PD | Predicate disambiguation | batch_69e514e5cb108190ae260e466c447314 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:44 p.m.