Triple
T28225846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puerto Banús |
E711581
|
entity |
| Predicate | distanceFromMarbella |
P201113
|
FINISHED |
| Object | approximately 6 kilometers southwest |
—
|
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 6 kilometers southwest | Statement: [Puerto Banús, distanceFromMarbella, approximately 6 kilometers southwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromMarbella Context triple: [Puerto Banús, distanceFromMarbella, approximately 6 kilometers southwest]
-
A.
distanceToMálaga
Indicates the spatial distance between a given entity and the location of Málaga.
-
B.
distanceFromSeville
Indicates the spatial distance separating an entity from the location of Seville.
-
C.
distanceFromCórdobaCity
Indicates the spatial distance between an entity and the city of Córdoba.
-
D.
distanceToMadrid
Indicates the physical distance between a given location or entity and the city of Madrid.
-
E.
distanceToMelilla
Indicates the measured spatial distance between an entity and the location of Melilla.
- 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_69efb51dfb048190ada79b745c33b363 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69ffc89596d08190b97bd60b45c7f9c0 |
completed | May 9, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69ffc81ba5dc8190ae94d44e2284948f |
completed | May 9, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ffc894cef481908dae1d9cdc7d9d1f |
completed | May 9, 2026, 11:51 p.m. |
Created at: April 27, 2026, 10:49 p.m.