Triple
T36993509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wûnseradiel |
E915166
|
entity |
| Predicate | usedLanguageOfficially |
P112296
|
FINISHED |
| Object | West Frisian place names |
—
|
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: West Frisian place names | Statement: [Wûnseradiel, usedLanguageOfficially, West Frisian place names]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedLanguageOfficially Context triple: [Wûnseradiel, usedLanguageOfficially, West Frisian place names]
-
A.
officialLanguage
Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
-
B.
hasLanguageOfficial
chosen
Indicates that a language holds official status within a given entity, such as a country, region, or organization.
-
C.
shareOfficialLanguage
Indicates that two entities have at least one official language in common.
-
D.
usesOfficialLanguageOf
Indicates that one entity adopts and employs the official language of another entity for communication or formal purposes.
-
E.
hasOfficialCountryLanguage
Indicates that a country recognizes a particular language as one of its official languages for governmental or legal purposes.
- 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_69f76e8f1a8c81909db172ed31304971 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb154c0fe08190a2e41e7a29b6055f |
completed | May 6, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_69f9fecc005c8190be082a8689193745 |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:14 p.m.