Triple
T14227271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Itezhi-Tezhi District |
E352654
|
entity |
| Predicate | seat |
P75
|
FINISHED |
| Object | Itezhi-Tezhi |
E1087109
|
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: Itezhi-Tezhi | Statement: [Itezhi-Tezhi District, seat, Itezhi-Tezhi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Itezhi-Tezhi Context triple: [Itezhi-Tezhi District, seat, Itezhi-Tezhi]
-
A.
Itezhi-Tezhi
chosen
Itezhi-Tezhi is a town in Zambia known for its proximity to the Itezhi-Tezhi Dam and Kafue National Park.
-
B.
Wedza
Wedza is a rural district and township in northeastern Zimbabwe known for its agriculture and gold deposits.
-
C.
Bafut
Bafut is a traditional kingdom and town in northwestern Cameroon known for its rich cultural heritage and historical palace.
-
D.
Oshikwanyama
Oshikwanyama is a Bantu language variety spoken primarily in northern Namibia and southern Angola, recognized as one of the major dialects of Oshiwambo.
-
E.
Masego
Masego is an American musician, singer, and producer known for his genre-blending "TrapHouseJazz" style that fuses jazz, R&B, and hip-hop.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de622a48508190bbfedb762bd1674d |
completed | April 14, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3251ec5881909fcebc9477d6a761 |
completed | May 8, 2026, 12:46 a.m. |
Created at: April 10, 2026, 1:07 a.m.