Triple
T19289918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albino |
E482412
|
entity |
| Predicate | distanceToBergamo |
P135145
|
FINISHED |
| Object | approximately 13 km northeast |
—
|
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 13 km northeast | Statement: [Albino, distanceToBergamo, approximately 13 km northeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBergamo Context triple: [Albino, distanceToBergamo, approximately 13 km northeast]
-
A.
distanceFromMilan
Indicates the spatial distance between a given entity and the city of Milan.
-
B.
distanceFromPavia
Indicates the spatial distance between a given entity or location and the city of Pavia.
-
C.
distanceToBari
Indicates the measured distance between a given entity (such as a place or object) and the location of Bari.
-
D.
distanceToVarese
Indicates the spatial distance between a given entity and the location of Varese.
-
E.
distanceToLecco
Indicates a relationship where one entity has a measurable distance or spatial separation to the location Lecco.
- 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_69d8e8cf61b0819096fe3e4107827c4e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc050a888190ac204d1e736200c5 |
completed | April 20, 2026, 10:12 a.m. |
| PD | Predicate disambiguation | batch_69e4dd0bc7508190a6f9d56bd4c3404f |
completed | April 19, 2026, 1:47 p.m. |
| PDg | Predicate description generation | batch_69e4ddcf50108190a09d0f1291c17374 |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 1:30 p.m.