Triple
T1392783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talpur dynasty |
E30597
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object |
Khairpur
Khairpur is a historic city in Sindh, Pakistan, known for its former princely state status under the Talpur rulers and its rich cultural and architectural heritage.
|
E160202
|
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: Khairpur | Statement: [Talpur dynasty, capital, Khairpur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khairpur Context triple: [Talpur dynasty, capital, Khairpur]
-
A.
Sialkot
Sialkot is a major industrial city in Pakistan’s Punjab province, renowned globally for its production of sports goods and surgical instruments.
-
B.
Nawabshah
Nawabshah is a major city in Pakistan known as an important commercial and agricultural center in the Sindh province.
-
C.
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.
-
D.
Haripur
Haripur is a city in northern Pakistan known as an administrative and commercial center in the Hazara region of Khyber Pakhtunkhwa.
-
E.
Jhang
Jhang is a historic city in the Punjab province of Pakistan, known for its cultural heritage and as the birthplace of several notable figures.
- 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: Khairpur Triple: [Talpur dynasty, capital, Khairpur]
Generated description
Khairpur is a historic city in Sindh, Pakistan, known for its former princely state status under the Talpur rulers and its rich cultural and architectural heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Khairpur Target entity description: Khairpur is a historic city in Sindh, Pakistan, known for its former princely state status under the Talpur rulers and its rich cultural and architectural heritage.
-
A.
Sialkot
Sialkot is a major industrial city in Pakistan’s Punjab province, renowned globally for its production of sports goods and surgical instruments.
-
B.
Nawabshah
Nawabshah is a major city in Pakistan known as an important commercial and agricultural center in the Sindh province.
-
C.
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.
-
D.
Haripur
Haripur is a city in northern Pakistan known as an administrative and commercial center in the Hazara region of Khyber Pakhtunkhwa.
-
E.
Jhang
Jhang is a historic city in the Punjab province of Pakistan, known for its cultural heritage and as the birthplace of several notable figures.
- 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_69a498fd4e408190bd73eca30ea9754c |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c360a7f08190ab7e903764b06fdf |
completed | March 1, 2026, 10:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acde28dd888190baa4a26f96f33e0a |
completed | March 8, 2026, 2:25 a.m. |
| NEDg | Description generation | batch_69acded118048190993aed439f1467ea |
completed | March 8, 2026, 2:28 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69acdf9b47b08190aaf348a32f6b9d2d |
completed | March 8, 2026, 2:31 a.m. |
Created at: March 1, 2026, 7:59 p.m.