Triple
T25697132
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ovada |
E644351
|
entity |
| Predicate | distanceToGenoa |
P51250
|
FINISHED |
| Object | about 35 kilometres |
—
|
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 35 kilometres | Statement: [Ovada, distanceToGenoa, about 35 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToGenoa Context triple: [Ovada, distanceToGenoa, about 35 kilometres]
-
A.
distanceToGenoa_km
chosen
Indicates the physical distance, measured in kilometers, between a given place or object and the city of Genoa.
-
B.
distanceToSavona_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Savona.
-
C.
distanceToVenice_km
Indicates the physical distance, measured in kilometers, between a given place and the city of Venice.
-
D.
distanceToTurin
Indicates the spatial distance between a given entity or location and the city of Turin.
-
E.
distanceFromTurin
Indicates the spatial distance separating an entity from the location of Turin.
- 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_69e77e82c9bc8190893090b2f6c64f1d |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fbad1e94988190b86d447a68e65067 |
completed | May 6, 2026, 9:05 p.m. |
| PD | Predicate disambiguation | batch_69fba881b8e0819094790935152b99a1 |
completed | May 6, 2026, 8:45 p.m. |
Created at: April 21, 2026, 8:38 p.m.