Triple
T19609415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Province, Zambia |
E470689
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Katete |
—
|
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: Katete | Statement: [Eastern Province, Zambia, hasTown, Katete]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katete Context triple: [Eastern Province, Zambia, hasTown, Katete]
-
A.
Katete
chosen
Katete is a town in eastern Zambia that serves as a key trading and transit hub near the border with Mozambique.
-
B.
Katenka
Katenka is a Russian diminutive form of the female given name Yekaterina (Catherine).
-
C.
Kaitish
Kaitish is an alternative name for the Kaytetye, an Aboriginal Australian people traditionally associated with the central Northern Territory.
-
D.
El Kabong
El Kabong is the masked, guitar-swinging vigilante alter ego of the cartoon horse sheriff Quick Draw McGraw from classic Hanna-Barbera animations.
-
E.
Katikati
Katikati is a small rural town in New Zealand known for its mural art, horticulture, and location near the Tauranga Harbour in the Bay of Plenty.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e510fa248190b7afb274a1d4cf73 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640ca57a081909c05000fca52271f |
completed | April 20, 2026, 3:05 p.m. |
Created at: April 10, 2026, 1:43 p.m.