Triple
T1078887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Frisian |
E23900
|
entity |
| Predicate | primaryTextType |
P5468
|
FINISHED |
| Object | legal texts |
—
|
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: legal texts | Statement: [Old Frisian, primaryTextType, legal texts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryTextType Context triple: [Old Frisian, primaryTextType, legal texts]
-
A.
textType
chosen
Indicates the classification of a text according to its type, format, or genre.
-
B.
primaryFront
Indicates that one entity serves as the main or most important front-facing side or surface in relation to another entity.
-
C.
primaryVariant
Indicates that one entity is the main or canonical version among multiple related variants of another entity.
-
D.
primaryMode
Indicates the main or most commonly used method, manner, or form in which an action, process, or interaction is carried out between entities.
-
E.
primaryContent
Indicates that one entity serves as the main or most important content associated with another entity.
- 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_69a493f1ddf48190a99d54b00e99f8ce |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b943b41481909b24050ca7e78971 |
completed | March 1, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69a4b73d9f08819093668104f129840e |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.