Triple
T15606521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinturicchio |
E375172
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Spello |
E186113
|
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: Spello | Statement: [Pinturicchio, workLocation, Spello]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spello Context triple: [Pinturicchio, workLocation, Spello]
-
A.
Spello
chosen
Spello is a picturesque medieval hill town in central Italy renowned for its well-preserved Roman and medieval architecture, narrow stone streets, and annual flower festival (Infiorate).
-
B.
Narni
Narni is a historic hilltop town in the Umbria region of central Italy, known for its medieval architecture and strategic position overlooking the Nera River valley.
-
C.
Aspelt
Aspelt is a small village in southern Luxembourg known for its historic church and castle remains.
-
D.
Holambra
Holambra is a Brazilian municipality in the state of São Paulo known for its Dutch heritage and large-scale flower production, earning it the nickname "City of Flowers."
-
E.
Montignoso
Montignoso is a municipality in Tuscany, central Italy, known for its coastal location near the Ligurian Sea and its proximity to the Apuan Alps.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e7ec08c8190b3842cf3043aea27 |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56d3541c8190a5a2aa9730260562 |
completed | May 9, 2026, 3:46 p.m. |
Created at: April 10, 2026, 4:13 a.m.