Triple
T17157064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morón Air Base |
E416369
|
entity |
| Predicate | distanceFromSeville |
P126335
|
FINISHED |
| Object | approximately 35 miles southeast |
—
|
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 35 miles southeast | Statement: [Morón Air Base, distanceFromSeville, approximately 35 miles southeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromSeville Context triple: [Morón Air Base, distanceFromSeville, approximately 35 miles southeast]
-
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.
distanceToMálaga
Indicates the spatial distance between a given entity and the location of Málaga.
-
D.
distanceToGranada
Indicates the spatial distance between a given entity or location and the city of Granada.
-
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_69d886d279c081909f8ff1f743ddeb69 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f40bf9ec8190b16372bcd091db9b |
completed | April 18, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69e3830d2a90819092386717dc56f0e8 |
completed | April 18, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69e3873f62108190966c4e741ebd548d |
completed | April 18, 2026, 1:29 p.m. |
Created at: April 10, 2026, 5:37 a.m.