Triple
T22704374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frans Kellendonk |
E561408
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Frans |
—
|
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: Frans | Statement: [Frans Kellendonk, givenName, Frans]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frans Context triple: [Frans Kellendonk, givenName, Frans]
-
A.
Frans
chosen
Frans is a common Dutch given name, notably borne by politician Frans Timmermans, a prominent European Union figure and former European Commission executive vice president.
-
B.
Francen
Francen is a surname most notably associated with Victor Francen, a Belgian-born actor prominent in early 20th-century European and American cinema.
-
C.
Flamand
Flamand is the idealistic young composer in Richard Strauss’s opera "Capriccio," representing the artistic and emotional power of music in the work’s central love and aesthetic debate.
-
D.
Frant
Frant is a village and civil parish in East Sussex, England, known for its historic church, traditional village green, and rural Wealden countryside setting.
-
E.
Belge
Belge is a Turkish surname most notably associated with journalist, politician, and diplomat Burhan Asaf Belge.
- 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_69e2454e615481909c177440be559d2c |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f178cca1e48190bbe7910f13692803 |
completed | April 29, 2026, 3:19 a.m. |
Created at: April 17, 2026, 3:16 p.m.