Triple
T22801094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saira Banu |
E564393
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Victoria No. 203 |
—
|
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: Victoria No. 203 | Statement: [Saira Banu, notableWork, Victoria No. 203]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Victoria No. 203 Context triple: [Saira Banu, notableWork, Victoria No. 203]
-
A.
Victoria No. 203
chosen
Victoria No. 203 is a 1972 Hindi crime-comedy film, best known as a popular caper movie featuring Ashok Kumar in a memorable role.
-
B.
Nao Victoria
Nao Victoria was the Spanish carrack that became the first ship to successfully circumnavigate the globe as part of Ferdinand Magellan’s expedition in the early 16th century.
-
C.
Liberty Victoria
Liberty Victoria is an Australian civil liberties and human rights advocacy organization based in Victoria.
-
D.
Victorias
Victorias is a city in the Philippine province of Negros Occidental known for its sugar industry and historic Victorias Milling Company.
-
E.
Sanai Victoria
Sanai Victoria is an American actress known for her roles in television series and films, including the family drama "Beaches" (2017).
- 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_69e2458185f88190b0045227ee420411 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17cdd87648190ba30f0b8f3ef7346 |
completed | April 29, 2026, 3:37 a.m. |
Created at: April 17, 2026, 3:31 p.m.