Triple
T26012670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pozos Azules |
E646942
|
entity |
| Predicate | distanceFromVillaDeLeyva |
P193289
|
FINISHED |
| Object | a few kilometers |
—
|
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 kilometers | Statement: [Pozos Azules, distanceFromVillaDeLeyva, a few kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromVillaDeLeyva Context triple: [Pozos Azules, distanceFromVillaDeLeyva, a few kilometers]
-
A.
distanceFromLleida
Indicates the spatial distance measured from the reference location of Lleida to another entity.
-
B.
distanceToLucenaCity_km
Indicates the distance, measured in kilometers, between a given entity’s location and Lucena City.
-
C.
distanceToLafia_km
Indicates the distance, measured in kilometers, from a given location or entity to Lafia.
-
D.
distanceFromCusco
Indicates the measured spatial distance between a given location or entity and the city of Cusco.
-
E.
distanceToHampi
Indicates the measured or specified distance between a given entity or location and Hampi.
- 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_69e77e8aa65881909ca58918f29ab2a0 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
| PDg | Predicate description generation | batch_69fd4128ed908190837ec9936774a1cf |
completed | May 8, 2026, 1:49 a.m. |
Created at: April 22, 2026, 9:02 a.m.