Triple
T30881560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samut Sakhon Province |
E786627
|
entity |
| Predicate | distanceToBangkok |
P29501
|
FINISHED |
| Object | approximately 30 kilometers southwest |
—
|
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 kilometers southwest | Statement: [Samut Sakhon Province, distanceToBangkok, approximately 30 kilometers southwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBangkok Context triple: [Samut Sakhon Province, distanceToBangkok, approximately 30 kilometers southwest]
-
A.
distanceFromBangkok
chosen
Indicates the spatial distance between a given location and the city of Bangkok.
-
B.
distanceFromThonBuriStation_km
Indicates the distance, measured in kilometers, between a given entity and Thon Buri Station.
-
C.
distanceFromPhuket
Indicates the measured distance between a given entity or location and Phuket.
-
D.
distanceFromPattaya
Indicates the spatial distance between a given place or object and the location of Pattaya.
-
E.
approximateDistanceInKilometersFromChiangMai
Indicates the approximate physical distance, measured in kilometers, between a given entity’s location and Chiang Mai.
- 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_69f224bae17c8190bb3a6a28e3d019df |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a016ebba0448190b5319243e1b2feca |
completed | May 11, 2026, 5:52 a.m. |
| PD | Predicate disambiguation | batch_6a016d2486b4819085efe197ee21b707 |
completed | May 11, 2026, 5:46 a.m. |
Created at: April 29, 2026, 8:48 p.m.