Triple
T6779535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Femke Halsema |
E155644
|
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.
Rineke
Rineke is a Dutch photographer renowned for her intimate, large-scale portraits that explore identity, vulnerability, and the passage of time.
-
E.
Saskia
Saskia is a female given name of Germanic origin, most famously borne by Saskia van Uylenburgh, the wife and frequent model of the Dutch painter Rembrandt.
- 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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d26a1634819099b8a3b3196a306a |
completed | March 27, 2026, 6:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c712cf86e08190bd07c98f01ac5e19 |
completed | March 27, 2026, 11:29 p.m. |
Created at: March 27, 2026, 2:14 p.m.