Triple
T14186641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Binnenmaas |
E351594
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Westmaas |
E1086283
|
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: Westmaas | Statement: [Binnenmaas, hasPart, Westmaas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Westmaas Context triple: [Binnenmaas, hasPart, Westmaas]
-
A.
Westmaas
chosen
Westmaas is a village in the Dutch province of South Holland, located on the island of Hoeksche Waard.
-
B.
Overijse
Overijse is a municipality in the Flemish Brabant province of Belgium, known for its green residential character and extensive vineyards.
-
C.
Wieringen
Wieringen is a former island and historical region in the Dutch province of North Holland, known for its coastal landscape and role in major water management projects like the Afsluitdijk.
-
D.
Salland
Salland is a historical and rural region in the Dutch province of Overijssel, known for its scenic landscapes, small towns, and agricultural character.
-
E.
Weiler-ter Meer
Weiler-ter Meer was a German chemical company that became part of the conglomerate IG Farben through a major industry merger.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61cd5778819092a03597bcdcc182 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd280861fc81908c342fc229a526f3 |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 10, 2026, 1:03 a.m.