Triple
T21417400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Fitzmaurice |
E528338
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Mata Hari |
E1406053
|
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: [George Fitzmaurice, notableWork, Mata Hari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mata Hari Context triple: [George Fitzmaurice, notableWork, Mata Hari]
-
A.
Mata Hari
chosen
Mata Hari was a famous Dutch exotic dancer and courtesan who became notorious as an accused spy during World War I.
-
B.
Mata Hari
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.
-
C.
Violette Heymann
Violette Heymann is the subject of a painted portrait, likely a woman of some social or cultural significance to the artist or period in which the work was created.
-
D.
Marie-Josèphe Yoyotte
Marie-Josèphe Yoyotte was a prominent French film editor known for her influential work on key films of the French New Wave and later French cinema.
-
E.
Ingrid Harrer
Ingrid Harrer was the wife of Austrian mountaineer and author Heinrich Harrer, known for his Himalayan expeditions and book "Seven Years in Tibet."
- 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_69e0c454c248819093425d1099101c09 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b2073a7881909adda8ed70a2cecd |
completed | April 22, 2026, 11:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09c8f7732c8190b5cfc41060c578f3 |
completed | May 17, 2026, 1:56 p.m. |
Created at: April 16, 2026, 5:46 p.m.