Triple
T30143513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sant Esteve Sesrovires |
E766188
|
entity |
| Predicate | distanceToMartorellInKilometres |
P202987
|
FINISHED |
| Object | about 5 |
—
|
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 5 | Statement: [Sant Esteve Sesrovires, distanceToMartorellInKilometres, about 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMartorellInKilometres Context triple: [Sant Esteve Sesrovires, distanceToMartorellInKilometres, about 5]
-
A.
distanceFromLleida
Indicates the spatial distance measured from the reference location of Lleida to another entity.
-
B.
distanceToBarcelonaKm
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Barcelona.
-
C.
distanceTo Palma de Mallorca (approximate km)
Indicates the approximate distance in kilometers between an entity’s location and Palma de Mallorca.
-
D.
distanceToMontpellierKm
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Montpellier.
-
E.
distanceToZaragoza
Indicates the spatial distance between a given entity or location and the city of Zaragoza.
- 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_69f2247909048190ae86c2160cf8b566 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a00d8ba18808190976682088a02a9a8 |
completed | May 10, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_6a00d85fad64819084f424ec8ecd3b57 |
completed | May 10, 2026, 7:11 p.m. |
| PDg | Predicate description generation | batch_6a00d8b8eac08190809c78998e09c47c |
completed | May 10, 2026, 7:12 p.m. |
Created at: April 29, 2026, 7:18 p.m.