Triple
T18767582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wat Ek Phnom |
E458929
|
entity |
| Predicate | distanceFromBattambang |
P133461
|
FINISHED |
| Object | approximately 11 km |
—
|
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 11 km | Statement: [Wat Ek Phnom, distanceFromBattambang, approximately 11 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromBattambang Context triple: [Wat Ek Phnom, distanceFromBattambang, approximately 11 km]
-
A.
distanceFromSiemReap
Indicates the measured distance between a given location and Siem Reap.
-
B.
distanceFromLuangPrabang
Indicates the spatial distance between a given location and Luang Prabang.
-
C.
approximateDistanceInKilometresFromLuangPrabang
Indicates the estimated distance, measured in kilometres, between an entity and the location of Luang Prabang.
-
D.
distanceFromSihanoukville
Indicates the measured distance between a given location and Sihanoukville.
-
E.
distanceFromAngkorWat
Indicates the spatial distance between a given location or entity and Angkor Wat.
- 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_69d8d395dba0819087568404508590cb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e58d859c8081909cec3aa64d264885 |
completed | April 20, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69e48d0b7b708190877951b6e6cdcbc4 |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49a9bcc0c81908df3e513fd6762ff |
completed | April 19, 2026, 9:04 a.m. |
Created at: April 10, 2026, 11:52 a.m.