Triple
T13076539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pak Ou Caves |
E329589
|
entity |
| Predicate | distanceFromLuangPrabang |
P108321
|
FINISHED |
| Object | approximately 25 kilometers |
—
|
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 25 kilometers | Statement: [Pak Ou Caves, distanceFromLuangPrabang, approximately 25 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromLuangPrabang Context triple: [Pak Ou Caves, distanceFromLuangPrabang, approximately 25 kilometers]
-
A.
distanceToVientiane_km
Indicates the physical distance, measured in kilometers, between a given location and Vientiane.
-
B.
distanceFromBangkok
Indicates the spatial distance between a given location and the city of Bangkok.
-
C.
distanceFromSihanoukville
Indicates the measured distance between a given location and Sihanoukville.
-
D.
distanceFromPattaya
Indicates the spatial distance between a given place or object and the location of Pattaya.
-
E.
distanceToHoChiMinhCity
Indicates the physical distance between a given location or entity and Ho Chi Minh City.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d98117209081908272021013df2222 |
completed | April 10, 2026, 11 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
| PDg | Predicate description generation | batch_69d980e622e8819087a69bfb1660dd64 |
completed | April 10, 2026, 10:59 p.m. |
Created at: April 9, 2026, 9:01 p.m.