Triple
T31822474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sơn Tây town |
E812298
|
entity |
| Predicate | distanceToHanoiCenter |
P188410
|
FINISHED |
| Object | approximately 35 km west |
—
|
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 35 km west | Statement: [Sơn Tây town, distanceToHanoiCenter, approximately 35 km west]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToHanoiCenter Context triple: [Sơn Tây town, distanceToHanoiCenter, approximately 35 km west]
-
A.
distanceToHanoiApprox
chosen
Indicates an approximate measure of the distance between a given location and Hanoi.
-
B.
distanceFromHanoi
Indicates the spatial distance between a given location and Hanoi.
-
C.
distanceFromHoiAnCenter
Indicates the measured distance between a given location and the central point of Hoi An.
-
D.
distanceFromHamilton
Indicates the spatial distance between a given entity and the location identified as Hamilton.
-
E.
roadDistanceToCityCentre_km
Indicates the distance in kilometers from a location to the city centre when traveling by road.
- 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_69f348e97fa48190aa06286962af6dee |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a0227ce59a081909fe1ba1181d86b4d |
completed | May 11, 2026, 7:02 p.m. |
| PD | Predicate disambiguation | batch_6a02273989208190beb948b8c7bdaee3 |
completed | May 11, 2026, 7 p.m. |
Created at: April 30, 2026, 11:46 p.m.