Triple
T14369879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maarten Baas |
E356331
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Maarten |
E411394
|
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: Maarten | Statement: [Maarten Baas, givenName, Maarten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maarten Context triple: [Maarten Baas, givenName, Maarten]
-
A.
Maarten
chosen
Maarten is a Dutch masculine given name, historically borne by notable figures such as the 17th-century admiral Maarten Tromp.
-
B.
Martijn
Martijn is a Dutch given name, commonly used as a variant of Martin in the Netherlands and other Dutch-speaking regions.
-
C.
Sebastiaan
Sebastiaan is a given name, primarily used in Dutch-speaking regions, that corresponds to the name Sébastien.
-
D.
Michiel
Michiel is a Dutch given name most famously borne by the 17th-century admiral Michiel de Ruyter.
-
E.
Wouter
Wouter is a Dutch historian of religion and leading scholar of Western esotericism.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8fb0b8988190ab834a85911c015c |
completed | April 14, 2026, 7:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c51bf888190b1776461884c4514 |
completed | May 8, 2026, 2:37 a.m. |
Created at: April 10, 2026, 1:15 a.m.