Triple
T21202584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheikhupura District |
E522493
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object |
Sheikhupura
Sheikhupura is a major city in Pakistan’s Punjab province known for its historical sites, including the Hiran Minar complex, and its role as an industrial and agricultural center.
|
E1473608
|
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: Sheikhupura | Statement: [Sheikhupura District, capital, Sheikhupura]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sheikhupura Context triple: [Sheikhupura District, capital, Sheikhupura]
-
A.
Lyallpur
Lyallpur, now known as Faisalabad, is a major industrial and agricultural city in Pakistan’s Punjab province.
-
B.
Muradnagar
Muradnagar is a town and municipal area in Uttar Pradesh, India, known for its proximity to Ghaziabad and its role as a local commercial and residential hub.
-
C.
Mauzamabad
Mauzamabad is a village-level settlement located within the Jaipur district of the Indian state of Rajasthan.
-
D.
Rajanpur
Rajanpur is a city in Pakistan known as an administrative and commercial center in the southern part of Punjab province.
-
E.
Shikarpur
Shikarpur is a historic city in the Sindh province of Pakistan, known for its old trading heritage and distinctive cultural and architectural traditions.
- 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: Sheikhupura Triple: [Sheikhupura District, capital, Sheikhupura]
Generated description
Sheikhupura is a major city in Pakistan’s Punjab province known for its historical sites, including the Hiran Minar complex, and its role as an industrial and agricultural center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sheikhupura Target entity description: Sheikhupura is a major city in Pakistan’s Punjab province known for its historical sites, including the Hiran Minar complex, and its role as an industrial and agricultural center.
-
A.
Lyallpur
Lyallpur, now known as Faisalabad, is a major industrial and agricultural city in Pakistan’s Punjab province.
-
B.
Muradnagar
Muradnagar is a town and municipal area in Uttar Pradesh, India, known for its proximity to Ghaziabad and its role as a local commercial and residential hub.
-
C.
Mauzamabad
Mauzamabad is a village-level settlement located within the Jaipur district of the Indian state of Rajasthan.
-
D.
Rajanpur
Rajanpur is a city in Pakistan known as an administrative and commercial center in the southern part of Punjab province.
-
E.
Shikarpur
Shikarpur is a historic city in the Sindh province of Pakistan, known for its old trading heritage and distinctive cultural and architectural traditions.
- 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73432a2b88190a89e636626d40c9b |
completed | April 21, 2026, 8:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0986e060188190b00ff5cc044c8208 |
completed | May 17, 2026, 9:14 a.m. |
| NEDg | Description generation | batch_6a0987a9ceac819083ecb7988661235a |
completed | May 17, 2026, 9:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09881c2d4c8190ab2cdf5dc99a43b0 |
completed | May 17, 2026, 9:19 a.m. |
Created at: April 16, 2026, 3:19 p.m.