Triple
T25710358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sétif Province |
E644711
|
entity |
| Predicate | subdivisionNameInFrench |
P114757
|
FINISHED |
| Object | Wilaya de Sétif |
—
|
NE NERFINISHED |
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: Wilaya de Sétif | Statement: [Sétif Province, subdivisionNameInFrench, Wilaya de Sétif]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subdivisionNameInFrench Context triple: [Sétif Province, subdivisionNameInFrench, Wilaya de Sétif]
-
A.
subdivisionNameFrench
chosen
Indicates the French-language name assigned to a specific administrative or geographic subdivision.
-
B.
subdivisionNameLanguage
Indicates the language in which the name of a subdivision (such as a region, district, or administrative unit) is expressed.
-
C.
subdivisionNameType
Indicates the type or category of a named geographic or administrative subdivision (e.g., province, state, district) associated with an entity.
-
D.
subdivisionNameLocal
Indicates the locally used or native-language name assigned to a specific administrative or geographic subdivision.
-
E.
subdivisionISOName
Indicates the standardized ISO-recognized name assigned to a specific administrative subdivision within a country.
- 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_69e77e83c8ec8190bf52fcdac4838984 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f62d89b89c8190afb372a8172111e7 |
completed | May 2, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69f62c1379f08190836c3e02b0c892df |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 21, 2026, 9:11 p.m.