Triple
T15661420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RCTP |
E376573
|
entity |
| Predicate | distanceFromTaipei |
P119638
|
FINISHED |
| Object | approximately 40 km west of Taipei |
—
|
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 40 km west of Taipei | Statement: [RCTP, distanceFromTaipei, approximately 40 km west of Taipei]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromTaipei Context triple: [RCTP, distanceFromTaipei, approximately 40 km west of Taipei]
-
A.
distanceFromTaiwanMainIsland
Indicates the measured spatial distance between an entity’s location and the main island of Taiwan.
-
B.
distanceFromKualaLumpur
Indicates the spatial distance between a given location or entity and Kuala Lumpur.
-
C.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
D.
distanceFromBeijingCityCenter
Indicates the physical distance between an entity’s location and the geographic center of Beijing city.
-
E.
distanceFromBeijing_km
Indicates the physical distance, measured in kilometers, between a given place or object and Beijing.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ef4e6a08190ad8bbafaa3612f22 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:15 a.m.