Triple
T839388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michiel de Ruyter |
E18142
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Vlissingen |
E250539
|
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: Vlissingen | Statement: [Michiel de Ruyter, placeOfBirth, Vlissingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vlissingen Context triple: [Michiel de Ruyter, placeOfBirth, Vlissingen]
-
A.
Vlissingen
chosen
Vlissingen is a historic port city on the North Sea coast of the Dutch province of Zeeland, known for its maritime heritage and seaside promenade.
-
B.
Hellevoetsluis
Hellevoetsluis is a historic Dutch port town known for its maritime heritage and coastal location in the western Netherlands.
-
C.
Terneuzen
Terneuzen is a port city and municipality in the southwestern Netherlands, known for its location on the Western Scheldt and its role in shipping access to the port of Ghent.
-
D.
Delfzijl
Delfzijl is a port town in the northeast of the Netherlands, known for its maritime industry and location on the Ems estuary near the German border.
-
E.
Katwijk
Katwijk is a coastal town and municipality in the western Netherlands known for its North Sea beaches and historic fishing heritage.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abe4ab1081909207ae2eec1898d9 |
completed | March 1, 2026, 9:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b528071e488190ac531404dac9587c |
completed | March 14, 2026, 9:19 a.m. |
Created at: March 1, 2026, 7:38 p.m.