Triple
T8032448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Castello di Vezio |
E187019
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Perledo |
E187023
|
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: Perledo | Statement: [Castello di Vezio, locatedIn, Perledo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Perledo Context triple: [Castello di Vezio, locatedIn, Perledo]
-
A.
Perledo
chosen
Perledo is a small Italian village in the Lombardy region overlooking Lake Como, known for its scenic hillside views near the town of Varenna.
-
B.
Perla
Perla is a Mexican telenovela best known for starring actress Silvia Navarro in one of her early prominent roles.
-
C.
La Perla
La Perla is a small municipality in the Mexican state of Veracruz that forms part of the Orizaba metropolitan area.
-
D.
La Perla
La Perla is a coastal urban district within the Lima metropolitan area of Peru, known for its dense residential neighborhoods and proximity to the Pacific Ocean.
-
E.
Diamaré
Diamaré is an administrative department in northern Cameroon, known for its role as a local governance and population center within the country’s Far North Region.
- 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_69ca82ae2d1081909dbfee42b41db419 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ef18da48190835454a5eb969da7 |
completed | March 31, 2026, 3:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc56e812dc81908916fc7163ae344a |
completed | March 31, 2026, 11:21 p.m. |
Created at: March 30, 2026, 5:22 p.m.