Triple
T29112501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Manyara |
E736949
|
entity |
| Predicate | distanceFromArusha |
P96998
|
FINISHED |
| Object | about 120 kilometers southwest |
—
|
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 120 kilometers southwest | Statement: [Lake Manyara, distanceFromArusha, about 120 kilometers southwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromArusha Context triple: [Lake Manyara, distanceFromArusha, about 120 kilometers southwest]
-
A.
distanceToArusha
chosen
Indicates the measured spatial distance between a given entity and the location Arusha.
-
B.
distanceFromKampala
Indicates the measured distance between a given location and the city of Kampala.
-
C.
distanceToAmboseliNationalPark
Indicates the measured or estimated spatial distance between a given entity and Amboseli National Park.
-
D.
distanceFromNairobi
Indicates the spatial distance between a given entity’s location and the city of Nairobi.
-
E.
distanceToMountKilimanjaro
Indicates the measured or estimated spatial distance between a given entity and Mount Kilimanjaro.
- F. None of above.
Provenance (3 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_69f077ed54e08190bb02a744e8121a66 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_6a0067cde0f08190b2cd93af5f00d519 |
completed | May 10, 2026, 11:11 a.m. |
| PD | Predicate disambiguation | batch_6a0065820c8c8190994734433c64a30a |
completed | May 10, 2026, 11:01 a.m. |
Created at: April 28, 2026, 11:19 a.m.