Triple
T3664760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramon Novarro |
E77733
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Mata Hari |
E309908
|
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: Mata Hari | Statement: [Ramon Novarro, notableWork, Mata Hari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mata Hari Context triple: [Ramon Novarro, notableWork, Mata Hari]
-
A.
Mata Hari
chosen
Mata Hari is a 1931 American pre-Code drama film starring Greta Garbo as an exotic dancer and spy, loosely inspired by the real-life World War I figure of the same name.
-
B.
Irma Zola
Irma Zola is a fictional character associated with the Marvel Comics universe, connected to the legacy of the villain Arnim Zola.
-
C.
Bernhardt
Bernhardt is a German-origin surname and given name, most famously associated with the legendary French stage actress Sarah Bernhardt.
-
D.
Yvonne Orlac
Yvonne Orlac is a central character in the 1935 horror film "Mad Love," serving as the wife of a famed pianist whose tragic circumstances draw her into a macabre tale of obsession and surgical horror.
-
E.
Rose Stradner
Rose Stradner was an Austrian-American actress known for her work in Hollywood films of the 1930s and 1940s.
- 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_69ad85dfc4dc8190a441864202ab2a7a |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc400352081908c16a6a7670eb52a |
completed | March 8, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b48848be788190acde46880918d36b |
completed | March 13, 2026, 9:57 p.m. |
Created at: March 8, 2026, 3:25 p.m.