Triple
T15145156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sadhu Bet |
E361785
|
entity |
| Predicate | distanceFromKevadia |
P117497
|
FINISHED |
| Object | approximately 1–2 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 1–2 km | Statement: [Sadhu Bet, distanceFromKevadia, approximately 1–2 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromKevadia Context triple: [Sadhu Bet, distanceFromKevadia, approximately 1–2 km]
-
A.
distanceFromKaunakakaiMiles
Indicates the physical distance, measured in miles, between an entity and the location of Kaunakakai.
-
B.
distanceFromGreenIsland
Indicates the measured distance separating a given entity or location from Green Island.
-
C.
distanceToKyushu
Indicates the spatial distance between a given entity’s location and the region of Kyushu.
-
D.
distanceToFidra
Indicates the spatial distance between a given entity and the reference location Fidra.
-
E.
distanceToPula
Indicates the measured or calculated spatial distance between a given entity and the location Pula.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005c71b688190b2e8ccfdf4db9037 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:07 a.m.