Triple
T393679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johan de Witt |
E8933
|
entity |
| Predicate | residence |
P75
|
FINISHED |
| Object | Dordrecht |
E40368
|
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: Dordrecht | Statement: [Johan de Witt, residence, Dordrecht]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dordrecht Context triple: [Johan de Witt, residence, Dordrecht]
-
A.
Dordrecht
chosen
Dordrecht is a historic Dutch city in South Holland known as one of the oldest trading centers in the Netherlands, situated strategically within the Rhine–Meuse–Scheldt river delta.
-
B.
Middelburg
Middelburg is a historic Dutch city in the province of Zeeland that served as an important maritime and trading center during the era of the Dutch East India Company.
-
C.
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.
-
D.
Groningen
Groningen is a historic province in the northern Netherlands, known for its university city of the same name, flat landscapes, and rich maritime and agricultural heritage.
-
E.
Rotterdam
Rotterdam is a major Dutch port city known for having one of the world’s largest harbors and striking modern architecture.
- 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec7637c08190b695ec640edbf6c2 |
completed | Feb. 28, 2026, 1:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7cf473e48819095390a5904429a9c |
completed | March 4, 2026, 6:20 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.