Triple
T10795750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wuqiu Township |
E254700
|
entity |
| Predicate | distanceToTaiwanMainIsland_km |
P71647
|
FINISHED |
| Object | over 150 |
—
|
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: over 150 | Statement: [Wuqiu Township, distanceToTaiwanMainIsland_km, over 150]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTaiwanMainIsland_km Context triple: [Wuqiu Township, distanceToTaiwanMainIsland_km, over 150]
-
A.
distanceFromTaiwanMainIsland
chosen
Indicates the measured spatial distance between an entity’s location and the main island of Taiwan.
-
B.
distanceFromMainland
Indicates the measured spatial separation between a location and the nearest point on the mainland.
-
C.
distanceToKoreanPeninsula
Indicates the measured or estimated spatial distance between a given entity or location and the Korean Peninsula.
-
D.
distanceFromKochi_km
Indicates the physical distance, measured in kilometers, between a given location and Kochi.
-
E.
distanceToPalikir
Indicates the spatial distance between a given location and Palikir.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d73332dbfc8190904434846957b618 |
completed | April 9, 2026, 5:03 a.m. |
| PD | Predicate disambiguation | batch_69d6f3188f00819094ee8d65b187a333 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.