Triple
T24279088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chaiya railway station |
E605488
|
entity |
| Predicate | distanceFromThonBuriStation_km |
P155646
|
FINISHED |
| Object | 603.0 |
—
|
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: 603.0 | Statement: [Chaiya railway station, distanceFromThonBuriStation_km, 603.0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromThonBuriStation_km Context triple: [Chaiya railway station, distanceFromThonBuriStation_km, 603.0]
-
A.
distanceFromBangkok
Indicates the spatial distance between a given location and the city of Bangkok.
-
B.
distanceFromPattayaCityCentre
Indicates the measured distance between a given location and the central area of Pattaya City.
-
C.
distanceFromPattaya
Indicates the spatial distance between a given place or object and the location of Pattaya.
-
D.
distanceToVientiane_km
Indicates the physical distance, measured in kilometers, between a given location and Vientiane.
-
E.
approximateDistanceInKilometresFromLuangPrabang
Indicates the estimated distance, measured in kilometres, between an entity and the location of Luang Prabang.
- F. None of above. chosen
Provenance (4 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_69e2954707dc8190915551eb114cfff6 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28f5032f48190a027e2d8b382ee79 |
completed | April 29, 2026, 11:08 p.m. |
| PD | Predicate disambiguation | batch_69f1c457a2908190993824395b3c365d |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f27a753ca8819095706970d368f762 |
completed | April 29, 2026, 9:39 p.m. |
Created at: April 18, 2026, 12:07 a.m.