Triple
T8974694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin |
E214356
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Martijn |
E360836
|
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: Martijn | Statement: [Martin, hasVariant, Martijn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martijn Context triple: [Martin, hasVariant, Martijn]
-
A.
Maarten
Maarten is a Dutch masculine given name, historically borne by notable figures such as the 17th-century admiral Maarten Tromp.
-
B.
Marius de Jonge
Marius de Jonge is a Dutch biblical scholar known for his influential work on New Testament studies and early Christianity.
-
C.
Michael Maarschalkerweerd
Michael Maarschalkerweerd was a prominent 19th-century Dutch organ builder known for founding the firm Maarschalkerweerd & Zoon and constructing notable church organs throughout the Netherlands.
-
D.
Maarten Baas
Maarten Baas is a Dutch designer and artist renowned for his conceptual, often playful furniture and installations that blur the boundaries between art and design.
-
E.
Jeroen
chosen
Jeroen is a common Dutch male given name, often associated internationally with figures such as politician Jeroen Dijsselbloem.
- 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_69ca839dbf608190a2f5990477115d29 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6783abe48190840e652fc2acf28f |
completed | April 1, 2026, 12:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc966f7d881908f4f80c2a0d820fe |
completed | April 3, 2026, 2:06 p.m. |
Created at: March 30, 2026, 7:02 p.m.