Triple
T13697996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sestriere |
E328437
|
entity |
| Predicate | distanceToTurin |
P111212
|
FINISHED |
| Object | about 100 kilometres |
—
|
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 100 kilometres | Statement: [Sestriere, distanceToTurin, about 100 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTurin Context triple: [Sestriere, distanceToTurin, about 100 kilometres]
-
A.
distanceFromTurin
Indicates the spatial distance separating an entity from the location of Turin.
-
B.
distanceFromMilan
Indicates the spatial distance between a given entity and the city of Milan.
-
C.
distanceToRome
Indicates the spatial distance between a given entity and the location of Rome.
-
D.
distanceToSavona_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Savona.
-
E.
distanceFromFlorence
Indicates the spatial distance between a given entity and the location of Florence.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc878b57c819094e7ea6d1a64211f |
completed | April 12, 2026, 4:29 p.m. |
| PD | Predicate disambiguation | batch_69dbbe9059488190a8113177c83e1481 |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:54 p.m.