Triple
T11276751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castelldefels |
E266955
|
entity |
| Predicate | distanceToBarcelona |
P74868
|
FINISHED |
| Object | about 20 km 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: about 20 km southwest | Statement: [Castelldefels, distanceToBarcelona, about 20 km southwest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBarcelona Context triple: [Castelldefels, distanceToBarcelona, about 20 km southwest]
-
A.
distanceToBarcelonaKm
chosen
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Barcelona.
-
B.
distanceToMadrid
Indicates the physical distance between a given location or entity and the city of Madrid.
-
C.
distanceToIbiza
Indicates the spatial distance between a given entity’s location and the location of Ibiza.
-
D.
distanceToPamplona
Indicates the spatial distance between a given entity and the location of Pamplona.
-
E.
distanceToMálaga
Indicates the spatial distance between a given entity and the location of Málaga.
- F. None of above.
Provenance (3 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_69d6aac8c2f48190ad0596f1f89f0470 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e967ebb4819080b09ed3cec44e77 |
completed | April 9, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69d787a240588190aa097298f951c915 |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:31 p.m.