Triple
T3726722
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amboseli National Park |
E81766
|
entity |
| Predicate | distanceFromNairobi |
P51265
|
FINISHED |
| Object | about 240 kilometers southeast of Nairobi |
—
|
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 240 kilometers southeast of Nairobi | Statement: [Amboseli National Park, distanceFromNairobi, about 240 kilometers southeast of Nairobi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromNairobi Context triple: [Amboseli National Park, distanceFromNairobi, about 240 kilometers southeast of Nairobi]
-
A.
distanceFromKampala
Indicates the measured distance between a given location and the city of Kampala.
-
B.
distanceFromMogadishu_km
Indicates the distance, measured in kilometers, between a given location and Mogadishu.
-
C.
distanceToKinshasa
Indicates the measured spatial distance between a given entity’s location and the city of Kinshasa.
-
D.
distanceToCairo_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Cairo.
-
E.
distanceFromCairo
Indicates the measured spatial distance between a given entity’s location and the city of Cairo.
- 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_69ad8b1b7ef081908d2d381bbf54985a |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcaf7a6908190bd0c3bb5c55ab9ee |
completed | March 8, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_69adc0452f5081909c79e114a86cce8c |
completed | March 8, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69adc226fffc81909c679b44e611fee6 |
completed | March 8, 2026, 6:38 p.m. |
Created at: March 8, 2026, 3:34 p.m.