Triple
T15671339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Geert Wilders |
E377318
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Geert |
E549889
|
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: Geert | Statement: [Geert Wilders, givenName, Geert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geert Context triple: [Geert Wilders, givenName, Geert]
-
A.
Geert
chosen
Geert is a masculine given name of Dutch origin commonly used in Belgium and the Netherlands.
-
B.
Goudriaan
Goudriaan is a small village in the Dutch province of South Holland, known for its rural character and historic polder landscape.
-
C.
Gijs
Gijs is a Dutch masculine given name commonly used in the Netherlands and Belgium.
-
D.
Jeroen
Jeroen is a common Dutch male given name, often associated internationally with figures such as politician Jeroen Dijsselbloem.
-
E.
Diederik
Diederik is a masculine given name of Dutch origin, notably borne by Dutch politician Diederik Samsom.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f13b1b08190beabc9f4098aa096 |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff67a431208190b7e0d1eefd55504a |
completed | May 9, 2026, 4:58 p.m. |
Created at: April 10, 2026, 4:16 a.m.