Triple
T13910455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Neeleman |
E334476
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Neeleman |
E60295
|
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: Neeleman | Statement: [Michael Neeleman, familyName, Neeleman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neeleman Context triple: [Michael Neeleman, familyName, Neeleman]
-
A.
Neeleman
chosen
Neeleman is a surname most notably associated with David Neeleman, the Brazilian-American entrepreneur and founder of multiple airlines including JetBlue Airways.
-
B.
Sjaalman
Sjaalman is a fictional character in Multatuli’s novel "Max Havelaar," serving as an alter ego and narrative device to expose colonial abuses in the Dutch East Indies.
-
C.
Molenaar
Molenaar is a Dutch occupational surname meaning "miller," referring to someone who operates or works at a mill.
-
D.
Danneels
Danneels is a Belgian surname most notably associated with Cardinal Godfried Danneels, a prominent Roman Catholic prelate and former Archbishop of Mechelen-Brussels.
-
E.
Van der Madeweg
Van der Madeweg is a metro station in Amsterdam that serves as a stop on the city's rapid transit network.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2723461881908376b5509ee0d530 |
completed | April 14, 2026, 11:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c72879e48190ac01d0a2023b098c |
completed | May 3, 2026, 10:07 p.m. |
Created at: April 9, 2026, 10:16 p.m.