Triple
T4321491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maser |
E96525
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Montebelluna |
E133263
|
NE 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: Montebelluna | Statement: [Maser, locatedNear, Montebelluna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montebelluna Context triple: [Maser, locatedNear, Montebelluna]
-
A.
Montebelluna
chosen
Montebelluna is a town in the Veneto region of northern Italy, known for its footwear industry and proximity to the foothills of the Dolomite mountains.
-
B.
Quarracino
Quarracino is an Italian-origin surname most notably associated with Argentine Cardinal Antonio Quarracino.
-
C.
Alpignano
Alpignano is a town in the Piedmont region of northwestern Italy, located near Turin in the Susa Valley.
-
D.
Blessagno
Blessagno is a small Italian village located in the mountainous Valle d’Intelvi area of Lombardy, near Lake Como.
-
E.
Sabbioneta
Sabbioneta is a Renaissance-era planned town in northern Italy renowned for its well-preserved urban layout, architecture, and cultural heritage.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69b345422aac81909ddbadae437d122e |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3511608dc8190afe912aa605ecace |
completed | March 12, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e4ef0ca881908d9811183adc26c4 |
completed | March 14, 2026, 10:45 p.m. |
Created at: March 12, 2026, 11:12 p.m.