Triple
T25697133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ovada |
E644351
|
entity |
| Predicate | distanceToAlessandria |
P188864
|
FINISHED |
| Object | about 40 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 40 kilometres | Statement: [Ovada, distanceToAlessandria, about 40 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToAlessandria Context triple: [Ovada, distanceToAlessandria, about 40 kilometres]
-
A.
distanceFromAlexandria_km
Indicates the distance, measured in kilometers, between a given location and Alexandria.
-
B.
distanceToApollonia
Indicates the measured spatial distance between a given entity and the location referred to as Apollonia.
-
C.
distanceToIalysos
Indicates a spatial relationship specifying the distance between a given entity and the location Ialysos.
-
D.
distanceToBrindisi
Indicates the measured or specified distance between a given entity or location and the city of Brindisi.
-
E.
distanceToPetra
Indicates the spatial distance between a given entity or location and Petra.
- 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_69e77e82c9bc8190893090b2f6c64f1d |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fbaf18085481908c774e8f8bbb9a41 |
completed | May 6, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
| PDg | Predicate description generation | batch_69fbaebbb7f88190b4edfd9b83550aad |
completed | May 6, 2026, 9:12 p.m. |
Created at: April 21, 2026, 8:38 p.m.