Triple
T1565013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiang Mai |
E33411
|
entity |
| Predicate | distanceFromBangkok |
P29501
|
FINISHED |
| Object | about 700 km north of Bangkok |
—
|
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: about 700 km north of Bangkok | Statement: [Chiang Mai, distanceFromBangkok, about 700 km north of Bangkok]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromBangkok Context triple: [Chiang Mai, distanceFromBangkok, about 700 km north of Bangkok]
-
A.
distanceFromTokyo
Indicates the physical distance between a given location and Tokyo.
-
B.
distanceFromStockholmCityCentre
Indicates the measured distance between a given location and the center of Stockholm city.
-
C.
distanceFromHanoi
Indicates the spatial distance between a given location and Hanoi.
-
D.
flightDistance
Indicates the measured distance covered by a flight between its origin and destination.
-
E.
distanceToBudapest_km
Indicates the physical distance, measured in kilometers, between a given location and Budapest.
- 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_69a885f11b048190935025a035302715 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90fccd4b48190a44012888a00af7f |
completed | March 5, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69a907b872f0819096b3df6ad502c63e |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a90fcb8ca48190a9ee50559ba73b22 |
completed | March 5, 2026, 5:08 a.m. |
Created at: March 4, 2026, 7:27 p.m.