Triple
T9054354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Libyan district system (pre‑2007) |
E216960
|
entity |
| Predicate | subdivisionNameInArabic |
P46025
|
FINISHED |
| Object | شعبية |
—
|
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: شعبية | Statement: [Libyan district system (pre‑2007), subdivisionNameInArabic, شعبية]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subdivisionNameInArabic Context triple: [Libyan district system (pre‑2007), subdivisionNameInArabic, شعبية]
-
A.
subdivisionNameLanguage
Indicates the language in which the name of a subdivision (such as a region, district, or administrative unit) is expressed.
-
B.
subdivisionNameLocal
chosen
Indicates the locally used or native-language name assigned to a specific administrative or geographic subdivision.
-
C.
subdivisionName0
Indicates the name assigned to the first (primary) subdivision or sub-unit associated with an entity.
-
D.
subdivisionISOName
Indicates the standardized ISO-recognized name assigned to a specific administrative subdivision within a country.
-
E.
subdivisionISONameLanguage
Indicates the language in which the ISO-standardized name of a geographic or administrative subdivision is expressed.
- 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_69ca83d362e88190ae44b4e4dc194209 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7a72e2dc8190a16deff8abe701b1 |
completed | April 1, 2026, 1:52 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee6d83c819095d8ed0779aa8511 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:10 p.m.