Triple
T2192484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eemsdelta |
E49893
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Loppersum |
E526403
|
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: Loppersum | Statement: [Eemsdelta, containsSettlement, Loppersum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loppersum Context triple: [Eemsdelta, containsSettlement, Loppersum]
-
A.
Loppersum
chosen
Loppersum is a village and former municipality in the province of Groningen in the Netherlands, known for its historic churches and its location in an area affected by gas-extraction-induced earthquakes.
-
B.
Veldhoven
Veldhoven is a town and municipality in the southern Netherlands, located near Eindhoven in the province of North Brabant.
-
C.
Zutphen
Zutphen is a historic city in the eastern Netherlands known for its well-preserved medieval center and location along the river IJssel.
-
D.
Hardinxveld-Giessendam
Hardinxveld-Giessendam is a Dutch town and municipality known for its shipbuilding industry and location along the river Merwede in the province of South Holland.
-
E.
Deurne
Deurne is a district of the Belgian city of Antwerp, known for its residential neighborhoods and green spaces such as Rivierenhof park.
- 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf48ceb48190956df39377df0548 |
completed | March 7, 2026, 6:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bfc0140a548190a9fb54c267622fb1 |
completed | March 22, 2026, 10:10 a.m. |
Created at: March 4, 2026, 7:46 p.m.