Triple
T17739641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banteay Srei |
E442818
|
entity |
| Predicate | distanceFromAngkorWat |
P128814
|
FINISHED |
| Object | about 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: about 25 kilometers | Statement: [Banteay Srei, distanceFromAngkorWat, about 25 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromAngkorWat Context triple: [Banteay Srei, distanceFromAngkorWat, about 25 kilometers]
-
A.
distanceFromSihanoukville
Indicates the measured distance between a given location and Sihanoukville.
-
B.
approximateDistanceInKilometresFromLuangPrabang
Indicates the estimated distance, measured in kilometres, between an entity and the location of Luang Prabang.
-
C.
distanceFromSesriem
Indicates the measured distance between a given location and Sesriem.
-
D.
distanceFromLuangPrabang
Indicates the spatial distance between a given location and Luang Prabang.
-
E.
distanceFromTikal
Indicates the spatial distance separating an entity from the location of Tikal.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47acb05848190a4b7edb98f15b8c6 |
completed | April 19, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69e3cde815e08190881972e2d80d151e |
completed | April 18, 2026, 6:31 p.m. |
| PDg | Predicate description generation | batch_69e3d37ab6988190bd326ea6f8dd4aaa |
completed | April 18, 2026, 6:54 p.m. |
Created at: April 10, 2026, 10:09 a.m.