Triple
T16978384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zaka District |
E411874
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Zaka |
E411879
|
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: Zaka | Statement: [Zaka District, hasCapital, Zaka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zaka Context triple: [Zaka District, hasCapital, Zaka]
-
A.
Zaka
chosen
Zaka is a rural district and administrative center located in southeastern Zimbabwe.
-
B.
Zekeria
Zekeria is an Afghan actor best known for his role in the film "The Kite Runner."
-
C.
Barkat
Barkat was one of the prominent martyrs of the Bengali Language Movement in East Bengal, remembered for sacrificing his life in the struggle to preserve the Bengali language and cultural identity.
-
D.
Fazza
Fazza is the popular pen name of Sheikh Hamdan bin Mohammed Al Maktoum, the Crown Prince of Dubai and a well-known Emirati poet and public figure.
-
E.
Askar
Askar is a coastal village in Bahrain known for its traditional fishing community and proximity to industrial and oil facilities.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d185a9408190a991bf8a1ef694f0 |
completed | April 18, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d477f7ec81909f1f0243004c9050 |
completed | May 10, 2026, 6:54 p.m. |
Created at: April 10, 2026, 5:32 a.m.