Triple
T36307098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diani Beach |
E893970
|
entity |
| Predicate | distanceFromMombasa |
P204823
|
FINISHED |
| Object | about 30 kilometers south |
—
|
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 30 kilometers south | Statement: [Diani Beach, distanceFromMombasa, about 30 kilometers south]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMombasa Context triple: [Diani Beach, distanceFromMombasa, about 30 kilometers south]
-
A.
distanceFromNairobi
Indicates the spatial distance between a given entity’s location and the city of Nairobi.
-
B.
distanceFromMogadishu
Indicates the spatial distance between a given location and Mogadishu.
-
C.
distanceFromMogadishu_km
Indicates the distance, measured in kilometers, between a given location and Mogadishu.
-
D.
approximateDistanceInKilometersToDarEsSalaam
Indicates the estimated distance, measured in kilometers, between a given entity’s location and the city of Dar es Salaam.
-
E.
distanceToAmboseliNationalPark
Indicates the measured or estimated spatial distance between a given entity and Amboseli National Park.
- 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_69f76e4c1b248190b10667d0213537fe |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:09 p.m.