Triple
T12982776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matara railway station |
E321692
|
entity |
| Predicate | hasApproximateDistanceToColomboByRail |
P65643
|
FINISHED |
| Object | about 160 km |
—
|
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: about 160 km | Statement: [Matara railway station, hasApproximateDistanceToColomboByRail, about 160 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateDistanceToColomboByRail Context triple: [Matara railway station, hasApproximateDistanceToColomboByRail, about 160 km]
-
A.
distanceToColombo
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.
distanceToByRail
chosen
Indicates the distance between two locations when traveling via railway routes.
-
D.
distanceToRailhead
Indicates the measured distance between a location or object and the nearest railhead (rail transport access point).
-
E.
distanceFromStation
Indicates the measured spatial separation between an entity and a specified station.
- 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_69d8076479b8819090afce3591939cdf |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97f2a71a0819098bb6cf8a4b2208a |
completed | April 10, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69d97dbdd94c8190ac4bbecca02dc77b |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:39 p.m.