Triple
T15028756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peniche |
E378285
|
entity |
| Predicate | distanceToBerlengas |
P116445
|
FINISHED |
| Object | approximately 10 to 15 kilometers |
—
|
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 to 15 kilometers | Statement: [Peniche, distanceToBerlengas, approximately 10 to 15 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBerlengas Context triple: [Peniche, distanceToBerlengas, approximately 10 to 15 kilometers]
-
A.
distanceToIbiza
Indicates the spatial distance between a given entity’s location and the location of Ibiza.
-
B.
distanceToLanzarote
Indicates the spatial distance between a given entity’s location and the location of Lanzarote.
-
C.
distanceFromMadeiraIsland
Indicates the spatial distance between an entity and Madeira Island.
-
D.
distanceFromSanSebastiánDeLaGomera
Indicates the measured distance between a given entity and the location San Sebastián de La Gomera.
-
E.
distanceFromSantaCruzDeTenerifeKm
Indicates the distance, measured in kilometers, between an entity and Santa Cruz de Tenerife.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7e0e8c88190ac6f5786b4d4040f |
completed | April 15, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69de9a67cbc481909c19c2de57de4eb7 |
completed | April 14, 2026, 7:50 p.m. |
| PDg | Predicate description generation | batch_69deb1a88d588190996afa8e5b32b552 |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:58 a.m.