Triple
T1358100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Femke Halsema |
E29035
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Femke |
E29035
|
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: Femke | Statement: [Femke Halsema, givenName, Femke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Femke Context triple: [Femke Halsema, givenName, Femke]
-
A.
Femke
chosen
Femke is a Dutch feminine given name, notably borne by politician Femke Halsema, the mayor of Amsterdam.
-
B.
Marijke
Marijke is the baptismal name of Princess Christina of the Netherlands, the youngest daughter of Queen Juliana and Prince Bernhard.
-
C.
Simone Buitendijk
Simone Buitendijk is a Dutch academic leader and scholar in higher education policy who has served as vice-chancellor of the University of Leeds.
-
D.
Annik Penders
Annik Penders is a Belgian communications professional best known as the wife of Belgian Prime Minister Alexander De Croo.
-
E.
Maayke Velders
Maayke Velders is known primarily as the spouse of Dutch naval hero Michiel de Ruyter.
- 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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c28f5b988190b0be4504eabb919d |
completed | March 1, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acce701a84819094815ab6e8383b76 |
completed | March 8, 2026, 1:18 a.m. |
Created at: March 1, 2026, 7:56 p.m.