Triple
T31062995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oleiros |
E791595
|
entity |
| Predicate | distanceTo A Coruña |
P203521
|
FINISHED |
| Object | approximately 10 km |
—
|
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: approximately 10 km | Statement: [Oleiros, distanceTo A Coruña, approximately 10 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceTo A Coruña Context triple: [Oleiros, distanceTo A Coruña, approximately 10 km]
-
A.
distanceToViana do Castelo
Indicates the spatial distance between a given entity and the location Viana do Castelo.
-
B.
distanceToSantander
Indicates the measured or calculated distance between a given entity (such as a location or point) and the city of Santander.
-
C.
distanceToBerlengas
Indicates the measured distance between a given entity’s location and the Berlengas.
-
D.
distanceToLanzarote
Indicates the spatial distance between a given entity’s location and the location of Lanzarote.
-
E.
distanceToValladolid
Indicates the spatial distance between a given entity or location and the city of Valladolid.
- 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_69f224cc0c5c81908404f087bff92997 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a019b8995dc819088727aa023beadce |
completed | May 11, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_6a01961bb748819096a941f1b5443908 |
completed | May 11, 2026, 8:40 a.m. |
| PDg | Predicate description generation | batch_6a019b88bbc88190924c1f0cdea6dd79 |
completed | May 11, 2026, 9:04 a.m. |
Created at: April 29, 2026, 9:01 p.m.