Triple
T3354769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | West Flemish |
E70578
|
entity |
| Predicate | hasMutualIntelligibility |
P7448
|
FINISHED |
| Object | partial with Standard Dutch |
—
|
LITERAL 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: partial with Standard Dutch | Statement: [West Flemish, hasMutualIntelligibility, partial with Standard Dutch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMutualIntelligibility Context triple: [West Flemish, hasMutualIntelligibility, partial with Standard Dutch]
-
A.
areMutuallyIntelligibleToSomeDegree
chosen
Indicates that two or more languages or communication systems can be at least partially understood by each other’s users without prior learning or translation.
-
B.
hasCommonLoanwordsFrom
Indicates that two languages share loanwords that originate from the same source language.
-
C.
hasNeighboringLanguages
Indicates that two languages are geographically or regionally adjacent to each other in their areas of use.
-
D.
hasDialectContinuumWith
Indicates that two languages or dialects are part of a continuous chain of mutually intelligible varieties, without a clear boundary separating them.
-
E.
isSpokenAs
Indicates that one entity is used as the spoken or verbal form of another entity (e.g., a word, name, or phrase).
- F. None of above.
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_69ad85a4ef7c8190a29e2bbd6fa454e4 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb24036848190bac779d17dfdce3b |
completed | March 8, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69ada42fbe7c8190b9f185b5ab985f17 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:13 p.m.