Triple
T20686657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quiripi language |
E508436
|
entity |
| Predicate | hasSourceLanguageForLoanwords |
P141048
|
FINISHED |
| Object | Dutch |
—
|
NE NERFINISHED |
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: Dutch | Statement: [Quiripi language, hasSourceLanguageForLoanwords, Dutch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dutch Context triple: [Quiripi language, hasSourceLanguageForLoanwords, Dutch]
-
A.
Dutch
Dutch is the nickname of Dutch Wagenbach, a tough, morally complex detective character from the television series "The Shield."
-
B.
Dutch
chosen
Dutch is a West Germanic language spoken primarily in the Netherlands and Belgium, serving as the basis for several regional and colonial varieties such as Flemish and Afrikaans.
-
C.
Dutch
Dutch is the battle-hardened special forces major portrayed by Arnold Schwarzenegger in the 1987 science fiction action film "Predator."
-
D.
Dutch
Dutch is a tough, heavy-weapons specialist and member of the Orbital Drop Shock Troopers (ODST) squad in the video game Halo 3: ODST.
-
E.
Nederlander
Nederlander is a prominent American theatrical family name best known for its multigenerational ownership and operation of major Broadway and live-entertainment venues.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c1ed408190b72dd26b1e33f8a1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6beacc30081908e57cd7f2c3ef047 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 11:45 a.m.