Triple
T16134841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Villa Gregoriana |
E391496
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Tivoli |
E88741
|
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: Tivoli | Statement: [Villa Gregoriana, locatedIn, Tivoli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tivoli Context triple: [Villa Gregoriana, locatedIn, Tivoli]
-
A.
Tivoli
chosen
Tivoli is an Italian hill town east of Rome renowned for its historic villas and gardens, including Emperor Hadrian’s vast imperial retreat, Hadrian’s Villa.
-
B.
Tivoli
Tivoli is an IBM software brand known for its enterprise systems management and monitoring solutions.
-
C.
Tivoli
Tivoli is a suburb within the city of Ipswich in Queensland, Australia, known for its residential character and proximity to the Bremer River.
-
D.
TivoliVredenburg
TivoliVredenburg is a large, modern music complex and cultural venue in Utrecht, Netherlands, known for its multiple concert halls and diverse live performances.
-
E.
Schmidt Tivoli
Schmidt Tivoli is a well-known theater and cabaret venue in Hamburg, Germany, famed for its variety shows and musical productions.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a04666c819091f36c5a2497d2e7 |
completed | April 17, 2026, 11:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff2b39bbc8190a2cb77a3f0a329fd |
completed | May 10, 2026, 2:51 a.m. |
Created at: April 10, 2026, 5:01 a.m.