Triple
T3259071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leiden Willeram |
E68366
|
entity |
| Predicate | originalLanguageRegion |
P10892
|
FINISHED |
| Object | Old Low Franconian area |
—
|
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: Old Low Franconian area | Statement: [Leiden Willeram, originalLanguageRegion, Old Low Franconian area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalLanguageRegion Context triple: [Leiden Willeram, originalLanguageRegion, Old Low Franconian area]
-
A.
originalLanguageCountry
Indicates the country where a work’s original language is primarily spoken or officially used.
-
B.
originalLanguageContext
Indicates the language in which something was first created or expressed, providing the original linguistic context for its content or meaning.
-
C.
originalLanguageSupport
Indicates that one entity provides or maintains functionality, content, or interaction in the original language of another entity.
-
D.
originalTitleLanguage
Indicates the language in which a work’s original title was written or expressed.
-
E.
regionLanguage
chosen
Indicates that a particular language is used or officially recognized within a specific geographic region.
- 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_69ad858f74408190bcbd07f967cd7bd0 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adafa4f40c81909adfd0f7f568e3ce |
completed | March 8, 2026, 5:19 p.m. |
| PD | Predicate disambiguation | batch_69ada41ae74081909a0d1d696be8e35e |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:09 p.m.