Triple
T25687830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neda waterfalls |
E644111
|
entity |
| Predicate | distanceFromNearestSettlement |
P144927
|
FINISHED |
| Object | a few kilometres from Figaleia |
—
|
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: a few kilometres from Figaleia | Statement: [Neda waterfalls, distanceFromNearestSettlement, a few kilometres from Figaleia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromNearestSettlement Context triple: [Neda waterfalls, distanceFromNearestSettlement, a few kilometres from Figaleia]
-
A.
distanceFromNearestSettlementKilometers
chosen
Indicates the distance, measured in kilometers, from an entity’s location to the closest human settlement.
-
B.
hasNearestLargerSettlement
Indicates that one settlement is associated with the geographically closest settlement that is larger in size or population.
-
C.
nearestTownDistance
Indicates the distance from a given location to the closest town.
-
D.
nearbySettlements
Indicates that one settlement is located close to another settlement in geographic space.
-
E.
distanceFromRegionalCapital
Indicates the measured spatial distance between a given place and its corresponding regional capital.
- 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_69e77e8046888190b07ffa58c7e2c37a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fba2877b248190a974eb092243c0c4 |
completed | May 6, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69fb8d06a1b48190a937aa410d159dfa |
completed | May 6, 2026, 6:48 p.m. |
Created at: April 21, 2026, 8:11 p.m.