Triple
T21983245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WebBrowser |
E542891
|
entity |
| Predicate | example |
P1259
|
FINISHED |
| Object | Opera |
—
|
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: Opera | Statement: [WebBrowser, example, Opera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Opera Context triple: [WebBrowser, example, Opera]
-
A.
Opera
chosen
Opera is a web browser known for its built-in features like a free VPN, ad blocker, and integrated messaging tools.
-
B.
Opera
Opera is a metro station on Cairo's Line 2 serving the downtown area near the Cairo Opera House and surrounding cultural landmarks.
-
C.
Opera
Opera is a historic Budapest Metro station located beneath Andrássy Avenue, serving the Hungarian State Opera House and the surrounding cultural district.
-
D.
Opera
Opera is a 1987 Italian horror film directed by Dario Argento, noted for its stylized violence and psychological terror set in the world of grand opera.
-
E.
Ópera
Ópera is a central Madrid Metro station located near the historic Teatro Real opera house and Plaza de Oriente.
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1270629588190aea32fbe630e4cba |
completed | April 28, 2026, 9:30 p.m. |
Created at: April 16, 2026, 8:04 p.m.