Triple
T10456888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nong Khai |
E246572
|
entity |
| Predicate | distanceToBangkok_km |
P29501
|
FINISHED |
| Object | approximately 620 |
—
|
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 620 | Statement: [Nong Khai, distanceToBangkok_km, approximately 620]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBangkok_km Context triple: [Nong Khai, distanceToBangkok_km, approximately 620]
-
A.
distanceFromBangkok
chosen
Indicates the spatial distance between a given location and the city of Bangkok.
-
B.
distanceFromPattaya
Indicates the spatial distance between a given place or object and the location of Pattaya.
-
C.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
D.
distanceFromBeijing_km
Indicates the physical distance, measured in kilometers, between a given place or object and Beijing.
-
E.
distanceToStockholmArlandaAirport
Indicates the measured distance between a given location or entity and Stockholm Arlanda Airport.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe498a808190b88530f0221df4a6 |
completed | April 7, 2026, 12:53 p.m. |
| PD | Predicate disambiguation | batch_69d4fb7d353c8190a73f439a956c7606 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:18 p.m.