Triple
T13697697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalutara South railway station |
E328429
|
entity |
| Predicate | distanceToColomboFortByRail_km |
P18161
|
FINISHED |
| Object | approximately 42 |
—
|
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 42 | Statement: [Kalutara South railway station, distanceToColomboFortByRail_km, approximately 42]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToColomboFortByRail_km Context triple: [Kalutara South railway station, distanceToColomboFortByRail_km, approximately 42]
-
A.
distanceToColombo
chosen
Indicates the measured or calculated spatial distance between a given entity’s location and the city of Colombo.
-
B.
distanceToSriLanka
Indicates the spatial distance between a given entity’s location and the country of Sri Lanka.
-
C.
directionFromColombo
Indicates the cardinal or relative compass direction of an entity’s location measured from Colombo.
-
D.
distanceToKandy_km
Indicates the physical distance, measured in kilometers, from a given location to Kandy.
-
E.
distanceToDelhiByRail_km
Indicates the distance, measured in kilometers, from a given place to Delhi when traveling by rail.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc878b57c819094e7ea6d1a64211f |
completed | April 12, 2026, 4:29 p.m. |
| PD | Predicate disambiguation | batch_69dbbe9059488190a8113177c83e1481 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:54 p.m.