Triple
T19628393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mawanella |
E471198
|
entity |
| Predicate | distanceToColomboByRoad_km |
P18161
|
FINISHED |
| Object | approximately 72 |
—
|
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 72 | Statement: [Mawanella, distanceToColomboByRoad_km, approximately 72]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToColomboByRoad_km Context triple: [Mawanella, distanceToColomboByRoad_km, approximately 72]
-
A.
distanceToColombo
chosen
Indicates the measured or calculated spatial distance between a given entity’s location and the city of Colombo.
-
B.
distanceToBatticaloa_km
Indicates the physical distance, measured in kilometers, between an entity’s location and Batticaloa.
-
C.
distanceFromGalle_km
Indicates the physical distance, measured in kilometers, between an entity and the location Galle.
-
D.
distanceToSriLanka
Indicates the spatial distance between a given entity’s location and the country of Sri Lanka.
-
E.
distanceToNegombo
Indicates the spatial distance between a given entity’s location and the location of Negombo.
- 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.