Triple
T21514949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bartolomeo Ammannati |
E530817
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Lucca |
—
|
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: Lucca | Statement: [Bartolomeo Ammannati, workLocation, Lucca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucca Context triple: [Bartolomeo Ammannati, workLocation, Lucca]
-
A.
Lucca
chosen
Lucca is a historic Tuscan city renowned for its well-preserved Renaissance walls, medieval architecture, and charming old town.
-
B.
Lucca
Lucca is a brilliant, bespectacled inventor and one of the main party members in the classic role-playing game Chrono Trigger.
-
C.
Veron
Veron is a microbiologist credited with formally naming and classifying the bacterial genus Campylobacter.
-
D.
Terenzo
Terenzo is a small municipality in the Province of Parma in Italy’s Emilia-Romagna region, known for its rural landscape and Apennine foothill setting.
-
E.
Parla
Parla is a suburban municipality and residential town located in the southern metropolitan area of Madrid, Spain.
- 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_69e0c45c81f08190a6b8bbb70a45aae7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea89b6e48190ac4ea139b895714f |
completed | April 23, 2026, 9:46 a.m. |
Created at: April 16, 2026, 6:25 p.m.