Triple
T12836582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eemsmond |
E306931
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Warffum |
E266403
|
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: Warffum | Statement: [Eemsmond, containsSettlement, Warffum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Warffum Context triple: [Eemsmond, containsSettlement, Warffum]
-
A.
Warffum
chosen
Warffum is a historic village in the Dutch province of Groningen, known for its traditional architecture and open-air museum showcasing rural life.
-
B.
Zandhoven
Zandhoven is a municipality in the Belgian province of Antwerp, known for its rural character and village communities.
-
C.
Zurenborg
Zurenborg is a historic and architecturally distinctive district in Antwerp, Belgium, renowned for its eclectic and Art Nouveau townhouses.
-
D.
Werthhoven
Werthhoven is a village-level district within the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
E.
Valkenburg
Valkenburg is a village in the Dutch province of South Holland, known for its historic charm and proximity to the North Sea coast.
- 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_69d7bdf52b94819096d6f0ba4ab50a98 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96ff015f4819090070a01f3938acc |
completed | April 10, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6af4f56108190b75dbf9bb144e94a |
completed | May 3, 2026, 2:13 a.m. |
Created at: April 9, 2026, 5:35 p.m.