Triple
T3293357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yobe State |
E69151
|
entity |
| Predicate | hasLocalGovernmentArea |
P8215
|
FINISHED |
| Object | Yusufari |
E345323
|
NE 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: Yusufari | Statement: [Yobe State, hasLocalGovernmentArea, Yusufari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yusufari Context triple: [Yobe State, hasLocalGovernmentArea, Yusufari]
-
A.
Husan
Husan is a Palestinian village located in the Bethlehem Governorate of the West Bank.
-
B.
Hasana
Hasana is a small town in Egypt’s North Sinai Governorate, situated in the Sinai Peninsula.
-
C.
Yunusari
chosen
Yunusari is a local government area in northeastern Nigeria, situated within Yobe State near the border with Niger.
-
D.
Haruna
Haruna was a Japanese Kongō-class fast battleship that served in the Imperial Japanese Navy during both World Wars and saw extensive action in the Pacific Theater.
-
E.
Sana'i
Sana'i was a pioneering 12th-century Persian Sufi poet whose mystical and didactic works profoundly shaped later poets, including Rumi.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb074f35081909dd3c8a09544b5f1 |
completed | March 8, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3cfec98819094208d2cb6e459ea |
completed | March 12, 2026, 5:11 p.m. |
Created at: March 8, 2026, 3:10 p.m.