Triple
T16799050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Balochistan |
E408306
|
entity |
| Predicate | majorTown |
P316
|
FINISHED |
| Object | Turbat |
—
|
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: Turbat | Statement: [Southern Balochistan, majorTown, Turbat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Turbat Context triple: [Southern Balochistan, majorTown, Turbat]
-
A.
Turbat
chosen
Turbat is a major city in southern Balochistan, Pakistan, known as a commercial and cultural center of the Makran region.
-
B.
Amarkot
Amarkot is an alternative name for Umarkot, a historic town and district in the Sindh province of Pakistan known for its cultural and Mughal-era significance.
-
C.
Shujabad
Shujabad is a city in southern Punjab, Pakistan, known for its agricultural economy and proximity to the regional center of Multan.
-
D.
Bannu
Bannu is a historic city in northwestern Pakistan known as a regional commercial and cultural center in the Khyber Pakhtunkhwa province.
-
E.
Multan
Multan is a historic city in southern Punjab, Pakistan, renowned as a major cultural, commercial, and Sufi spiritual center with a legacy spanning over two millennia.
- 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_69d88393905081908d00a86b99996ac8 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2abc430819080c1303eded5f416 |
completed | April 18, 2026, 4:34 p.m. |
Created at: April 10, 2026, 5:22 a.m.