Triple
T4651803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balochistan, Pakistan |
E102310
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Turbat
Turbat is a major city in southern Balochistan, Pakistan, known as a commercial and cultural center of the Makran region.
|
E483983
|
NE FINISHED |
How this triple was built (4 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: [Balochistan, Pakistan, containsCity, Turbat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Turbat Context triple: [Balochistan, Pakistan, containsCity, Turbat]
-
A.
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.
-
B.
Shujabad
Shujabad is a city in southern Punjab, Pakistan, known for its agricultural economy and proximity to the regional center of Multan.
-
C.
Bannu
Bannu is a historic city in northwestern Pakistan known as a regional commercial and cultural center in the Khyber Pakhtunkhwa province.
-
D.
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.
-
E.
Bahawalnagar
Bahawalnagar is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub near the border with India.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Turbat Triple: [Balochistan, Pakistan, containsCity, Turbat]
Generated description
Turbat is a major city in southern Balochistan, Pakistan, known as a commercial and cultural center of the Makran region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Turbat Target entity description: Turbat is a major city in southern Balochistan, Pakistan, known as a commercial and cultural center of the Makran region.
-
A.
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.
-
B.
Shujabad
Shujabad is a city in southern Punjab, Pakistan, known for its agricultural economy and proximity to the regional center of Multan.
-
C.
Bannu
Bannu is a historic city in northwestern Pakistan known as a regional commercial and cultural center in the Khyber Pakhtunkhwa province.
-
D.
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.
-
E.
Bahawalnagar
Bahawalnagar is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub near the border with India.
- F. None of above. chosen
Provenance (5 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_69bd43d71a308190afea7280841b0de8 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd630343f88190954d19fcd18a5864 |
completed | March 20, 2026, 3:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be89c2485881908797f4a3560a0b04 |
completed | March 21, 2026, 12:06 p.m. |
| NEDg | Description generation | batch_69be8aaa3eac8190876fc8c892cb7c3f |
completed | March 21, 2026, 12:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69be8b164c8c8190b03e7e4892b6aa9e |
completed | March 21, 2026, 12:12 p.m. |
Created at: March 20, 2026, 1:14 p.m.