Triple
T15138707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sagunto |
E361624
|
entity |
| Predicate | distanceToValencia |
P117469
|
FINISHED |
| Object | about 25 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 25 kilometres | Statement: [Sagunto, distanceToValencia, about 25 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToValencia Context triple: [Sagunto, distanceToValencia, about 25 kilometres]
-
A.
distanceToValladolid
Indicates the spatial distance between a given entity or location and the city of Valladolid.
-
B.
distanceToMadrid
Indicates the physical distance between a given location or entity and the city of Madrid.
-
C.
distanceFromLleida
Indicates the spatial distance measured from the reference location of Lleida to another entity.
-
D.
distanceToZaragoza
Indicates the spatial distance between a given entity or location and the city of Zaragoza.
-
E.
distanceFromCórdobaCity
Indicates the spatial distance between an entity and the city of Córdoba.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005b59b488190b0016970647e7483 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:07 a.m.