Triple
T14981366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montasola |
E373582
|
entity |
| Predicate | sharesBorderWith |
P224
|
FINISHED |
| Object | Casperia |
E344564
|
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: Casperia | Statement: [Montasola, sharesBorderWith, Casperia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Casperia Context triple: [Montasola, sharesBorderWith, Casperia]
-
A.
Casperia
chosen
Casperia is a historic hilltop village in central Italy’s Lazio region, known for its medieval architecture and panoramic views over the Sabine countryside.
-
B.
Pastoria
Pastoria is the former king of the Land of Oz and the father of Princess Ozma in L. Frank Baum’s Oz series.
-
C.
Tarusa
Tarusa is a small historic town in western Russia known for its scenic location on the Oka River and its associations with Russian artists and writers.
-
D.
Valdosta
Valdosta is a city in southern Georgia known as a regional commercial hub and home to Valdosta State University.
-
E.
Copertino
Copertino is a historic town in Italy’s Apulia region, known for its medieval castle and as the birthplace of Saint Joseph of Cupertino.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6fe42a081909308f788fdf024d5 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8bef015c8190bdfb1b9144b2a55c |
completed | May 9, 2026, 1:20 a.m. |
Created at: April 10, 2026, 2:52 a.m.