Triple
T6786184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maarten Tromp |
E155808
|
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 Tromp, givenName, Maarten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maarten Context triple: [Maarten Tromp, 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.
Michiel
Michiel is a Dutch given name most famously borne by the 17th-century admiral Michiel de Ruyter.
-
C.
Wouter
Wouter is a Dutch historian of religion and leading scholar of Western esotericism.
-
D.
Adriaan
Adriaan is a masculine given name of Dutch origin commonly used in the Netherlands and other Dutch-speaking regions.
-
E.
Dirck
Dirck is a Dutch masculine given name historically borne by several notable figures, including artists of the Dutch Golden Age.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d28f043081909a9a9ab635785933 |
completed | March 27, 2026, 6:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723cc35cc8190b5affdfd363171ba |
completed | March 28, 2026, 12:41 a.m. |
Created at: March 27, 2026, 2:14 p.m.