Triple
T6543124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koh Tang |
E168338
|
entity |
| Predicate | distanceFromSihanoukville |
P72292
|
FINISHED |
| Object | approximately 52–60 km southwest of Sihanoukville |
—
|
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 52–60 km southwest of Sihanoukville | Statement: [Koh Tang, distanceFromSihanoukville, approximately 52–60 km southwest of Sihanoukville]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromSihanoukville Context triple: [Koh Tang, distanceFromSihanoukville, approximately 52–60 km southwest of Sihanoukville]
-
A.
distanceToHoChiMinhCity
Indicates the physical distance between a given location or entity and Ho Chi Minh City.
-
B.
distanceFromHanoi
Indicates the spatial distance between a given location and Hanoi.
-
C.
distanceToHoniaraApprox
Indicates an approximate distance measurement between a given entity’s location and the location of Honiara.
-
D.
distanceFromGeorgeTown
Indicates the measured spatial distance between a given location and George Town.
-
E.
distanceToPort-au-Prince
Indicates the spatial distance between a given location and the city of Port-au-Prince.
- 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_69c68a51564081909e93aee0dbd9cca3 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6ce07332481909a5a7964282eb776 |
completed | March 27, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69c6acf3e3708190b052ec774e607cb7 |
completed | March 27, 2026, 4:14 p.m. |
| PDg | Predicate description generation | batch_69c6ce0538f48190abf3160681901c17 |
completed | March 27, 2026, 6:35 p.m. |
Created at: March 27, 2026, 1:50 p.m.