Triple
T8074074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simiyu Region |
E188448
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Bariadi |
E667762
|
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: Bariadi | Statement: [Simiyu Region, capital, Bariadi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bariadi Context triple: [Simiyu Region, capital, Bariadi]
-
A.
Bariadi
chosen
Bariadi is a town in northern Tanzania that serves as an important local administrative and commercial center.
-
B.
Barara
Barara is a town in the Ambala district of the northern Indian state of Haryana, known primarily as a local administrative and market center for surrounding rural areas.
-
C.
Bara
Bara is a town in Pakistan’s Khyber District, known as a key settlement in the Khyber Pass region with strategic and commercial significance.
-
D.
Barshaini
Barshaini is a small Himalayan village in Himachal Pradesh, India, that serves as a popular base and trailhead for treks into the Parvati Valley and surrounding high-altitude landscapes.
-
E.
Baniata
Baniata is an Oceanic language of the Meso-Melanesian group spoken in the Solomon Islands.
- 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_69ca82b50c708190863f661d438e68df |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb404a98408190b6c8eecb95ad086d |
completed | March 31, 2026, 3:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63f000308190a55379f8bf67f0cd |
completed | April 1, 2026, 12:16 a.m. |
Created at: March 30, 2026, 5:27 p.m.