Triple
T21305100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alessandro Antonelli |
E525173
|
entity |
| Predicate | hasWorkIn |
P17879
|
FINISHED |
| Object | Ghemme |
—
|
NE NERFINISHED |
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: Ghemme | Statement: [Alessandro Antonelli, hasWorkIn, Ghemme]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ghemme Context triple: [Alessandro Antonelli, hasWorkIn, Ghemme]
-
A.
Ghemme
chosen
Ghemme is a small town in Italy’s Piedmont region, known for its historic architecture and production of Nebbiolo-based wines.
-
B.
Gemer
Gemer is a historical and geographical region in southern Slovakia known for its mining heritage, medieval castles, and karst landscapes.
-
C.
Ganguise
Ganguise is a watercourse in southern France that feeds the artificial reservoir known as Lac de la Ganguise.
-
D.
Gemerek
Gemerek is a town and district in central Turkey known for its location within Sivas Province on the Anatolian plateau.
-
E.
De Meent
De Meent is a central shopping center in the Dutch town of Papendrecht, offering a variety of retail stores and services.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b518b8948190ad69cf9a8784d397 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e75aa341908190963c4368708860b8 |
completed | April 21, 2026, 11:08 a.m. |
Created at: April 16, 2026, 4:05 p.m.