Triple
T13314535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lleida–Alguaire Airport |
E317155
|
entity |
| Predicate | distanceFromLleida |
P109470
|
FINISHED |
| Object | approximately 15 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 15 km | Statement: [Lleida–Alguaire Airport, distanceFromLleida, approximately 15 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromLleida Context triple: [Lleida–Alguaire Airport, distanceFromLleida, approximately 15 km]
-
A.
distanceFromCórdobaCity
Indicates the spatial distance between an entity and the city of Córdoba.
-
B.
distanceToMadrid
Indicates the physical distance between a given location or entity and the city of Madrid.
-
C.
distanceToZaragoza
Indicates the spatial distance between a given entity or location and the city of Zaragoza.
-
D.
distanceToBarcelonaKm
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Barcelona.
-
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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6babd88190a5d529df9584b9a4 |
completed | April 11, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69d99cf7f9c48190a6a4f452b4a2aefa |
completed | April 11, 2026, 12:59 a.m. |
Created at: April 9, 2026, 9:29 p.m.