Triple
T12447425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Toni Merkens |
E297437
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Merkens |
E297437
|
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: Merkens | Statement: [Toni Merkens, familyName, Merkens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Merkens Context triple: [Toni Merkens, familyName, Merkens]
-
A.
Merkens
chosen
Merkens is a German surname most notably associated with Olympic track cyclist Toni Merkens.
-
B.
Merkys
Merkys is a river in Lithuania and Belarus that serves as one of the principal tributaries of the Neman (Niemen) River.
-
C.
Merksem
Merksem is a northern district of the Belgian city of Antwerp, known as a predominantly residential area with local commerce and sports facilities.
-
D.
Mieresch
Mieresch is the German name for the Mureș River, a major river flowing through Romania and Hungary.
-
E.
Minkels
Minkels is a data center infrastructure brand known for its modular server racks, cooling solutions, and cable management systems, now part of the Legrand group.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d90f18c819083a36ff4b9be4a20 |
completed | April 10, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f132d048190b58a8381bdc74cad |
completed | May 2, 2026, 6:14 p.m. |
Created at: April 8, 2026, 9:56 p.m.