Triple
T4909415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rineke Dijkstra |
E110195
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Sittard |
E454917
|
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: Sittard | Statement: [Rineke Dijkstra, placeOfBirth, Sittard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sittard Context triple: [Rineke Dijkstra, placeOfBirth, Sittard]
-
A.
Harderwijk
Harderwijk is a historic Dutch city known for its former Hanseatic trading role and scenic location on the shores of the Veluwemeer.
-
B.
Wijchen
Wijchen is a town and municipality in the Dutch province of Gelderland, located just southwest of the city of Nijmegen.
-
C.
Schoonhoven
Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
-
D.
Gorinchem
Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
-
E.
Sittard-Geleen
chosen
Sittard-Geleen is a municipality and city in the southern Netherlands known for its historic town centers and location near the German and Belgian borders.
- 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_69bd44132b94819088522d92beaadc78 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e99414081908c3d3283f563bba4 |
completed | March 20, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e343941ae481909489cf7a4abdba68 |
completed | April 18, 2026, 8:40 a.m. |
Created at: March 20, 2026, 1:29 p.m.