Triple
T14847534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zia Mohyeddin |
E349136
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object |
Lyallpur
Lyallpur, now known as Faisalabad, is a major industrial and agricultural city in Pakistan’s Punjab province.
|
E1134169
|
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: Lyallpur | Statement: [Zia Mohyeddin, placeOfBirth, Lyallpur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lyallpur Context triple: [Zia Mohyeddin, placeOfBirth, Lyallpur]
-
A.
Narowal
Narowal is a city in the Punjab province of Pakistan, located close to the border with India and known for its agricultural surroundings and proximity to the Ravi River.
-
B.
Baldia Town
Baldia Town is a residential and industrial locality in the western part of Karachi, Pakistan, known for its dense population and proximity to major industrial zones.
-
C.
Gujranwala
Gujranwala is a major industrial city in Pakistan’s Punjab province, known for its manufacturing base and historical significance in the region.
-
D.
Rajanpur
Rajanpur is a city in Pakistan known as an administrative and commercial center in the southern part of Punjab province.
-
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: Lyallpur Triple: [Zia Mohyeddin, placeOfBirth, Lyallpur]
Generated description
Lyallpur, now known as Faisalabad, is a major industrial and agricultural city in Pakistan’s Punjab province.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lyallpur Target entity description: Lyallpur, now known as Faisalabad, is a major industrial and agricultural city in Pakistan’s Punjab province.
-
A.
Narowal
Narowal is a city in the Punjab province of Pakistan, located close to the border with India and known for its agricultural surroundings and proximity to the Ravi River.
-
B.
Baldia Town
Baldia Town is a residential and industrial locality in the western part of Karachi, Pakistan, known for its dense population and proximity to major industrial zones.
-
C.
Gujranwala
Gujranwala is a major industrial city in Pakistan’s Punjab province, known for its manufacturing base and historical significance in the region.
-
D.
Rajanpur
Rajanpur is a city in Pakistan known as an administrative and commercial center in the southern part of Punjab province.
-
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_69d822ec69008190a9232caa68836872 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded29236dc8190b7d3a37d09f9fb21 |
completed | April 14, 2026, 11:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dbf1f5c8190ad4626d14e0d8109 |
completed | May 9, 2026, 2:36 a.m. |
| NEDg | Description generation | batch_69fea10834ac8190b4fbd0a165439110 |
completed | May 9, 2026, 2:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fea19745c08190b0efd33ee3f97fe1 |
completed | May 9, 2026, 2:53 a.m. |
Created at: April 10, 2026, 1:53 a.m.