Triple
T3933891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dommel |
E90861
|
entity |
| Predicate | tributaryOf |
P415
|
FINISHED |
| Object | Dieze |
E399687
|
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: Dieze | Statement: [Dommel, tributaryOf, Dieze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dieze Context triple: [Dommel, tributaryOf, Dieze]
-
A.
Dieze
chosen
The Dieze is a river in the southern Netherlands that flows through the city of ’s-Hertogenbosch and ultimately drains into the Dommel and Aa river system.
-
B.
Dezamet
Dezamet is a Polish defense manufacturer known for producing munitions and military equipment for the country’s armed forces and export markets.
-
C.
Kwintsheul
Kwintsheul is a village in the Dutch province of South Holland, known for its greenhouse horticulture and location within the Westland region.
-
D.
Zeil
Zeil is Frankfurt am Main’s main shopping street, known as one of Germany’s busiest and most popular retail boulevards.
-
E.
Tuineje
Tuineje is a coastal municipality on the island of Fuerteventura in Spain’s Canary Islands, known for its rural landscapes, beaches, and traditional Canarian culture.
- 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_69aed95f26e0819094b0e71974543a19 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeedcab1808190bf653f29062cdddb |
completed | March 9, 2026, 3:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5338afa348190bc5ac0b0319c6e45 |
completed | March 14, 2026, 10:08 a.m. |
Created at: March 9, 2026, 3:23 p.m.