Triple
T5422899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Picard language |
E121293
|
entity |
| Predicate | countryVariant |
P63571
|
FINISHED |
| Object | French Picard |
—
|
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: French Picard | Statement: [Picard language, countryVariant, French Picard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryVariant Context triple: [Picard language, countryVariant, French Picard]
-
A.
countryFeatured
Indicates that a particular country is highlighted or given special prominence in a given context or presentation.
-
B.
countryOrRegion
Indicates that one entity is a country or geographic region associated with another entity (such as its location, jurisdiction, or area of relevance).
-
C.
countryLabel
Indicates the name or label of the country associated with an entity.
-
D.
countryStatus
Indicates the political or legal condition of a country, such as its sovereignty, recognition, or current state in international or domestic contexts.
-
E.
countryRegion
Indicates that a country is located within, or belongs to, a specific geographic or administrative region.
- F. None of above. chosen
Provenance (4 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_69bd463b58d88190b258261573de9e91 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8812f84c819094d8516f69fff83d |
completed | March 20, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69bd8469f5e48190bbe5c8bdfe8925ea |
completed | March 20, 2026, 5:31 p.m. |
| PDg | Predicate description generation | batch_69bd8741e8588190863fd5cfb559136d |
completed | March 20, 2026, 5:43 p.m. |
Created at: March 20, 2026, 2:06 p.m.