Triple
T4572360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bishopric of Vlaardingen |
E123060
|
entity |
| Predicate | usedVernacularLanguage |
P18209
|
FINISHED |
| Object | Middle 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: Middle Dutch | Statement: [Bishopric of Vlaardingen, usedVernacularLanguage, Middle Dutch]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedVernacularLanguage Context triple: [Bishopric of Vlaardingen, usedVernacularLanguage, Middle Dutch]
-
A.
languageUse
chosen
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
B.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
-
C.
officialLanguageUse
Indicates that a particular language is formally designated and used by an authority (such as a government or institution) for official communication, documentation, or functions.
-
D.
nativeLanguage
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
E.
primaryLanguageVariety
Indicates the main dialect or specific variety of a language that an entity primarily uses.
- 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58c711408190a2b096daf57e6eac |
completed | March 20, 2026, 2:25 p.m. |
| PD | Predicate disambiguation | batch_69bd5227063c8190973155a875b013a7 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:10 p.m.