Triple
T12607994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khushab nuclear complex |
E301033
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object |
Jauharabad
Jauharabad is a planned town in Pakistan’s Punjab province, known for its proximity to key industrial and strategic facilities.
|
E1003863
|
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: Jauharabad | Statement: [Khushab nuclear complex, near, Jauharabad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jauharabad Context triple: [Khushab nuclear complex, near, Jauharabad]
-
A.
Wazirabad
Wazirabad is a city in the Gujranwala District of Punjab, Pakistan, known for its cutlery industry and strategic location near the Chenab River.
-
B.
Haroonabad
Haroonabad is a town in Pakistan known for its agricultural surroundings and role as a local commercial center.
-
C.
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.
-
D.
Jamshoro
Jamshoro is a city in the Sindh province of Pakistan known as an important educational hub, hosting several major universities and research institutions.
-
E.
Shahabad
Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
- 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: Jauharabad Triple: [Khushab nuclear complex, near, Jauharabad]
Generated description
Jauharabad is a planned town in Pakistan’s Punjab province, known for its proximity to key industrial and strategic facilities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Jauharabad Target entity description: Jauharabad is a planned town in Pakistan’s Punjab province, known for its proximity to key industrial and strategic facilities.
-
A.
Wazirabad
Wazirabad is a city in the Gujranwala District of Punjab, Pakistan, known for its cutlery industry and strategic location near the Chenab River.
-
B.
Haroonabad
Haroonabad is a town in Pakistan known for its agricultural surroundings and role as a local commercial center.
-
C.
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.
-
D.
Jamshoro
Jamshoro is a city in the Sindh province of Pakistan known as an important educational hub, hosting several major universities and research institutions.
-
E.
Shahabad
Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954e90efc81909951dbe698afa851 |
completed | April 10, 2026, 7:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ea99ac88190bc0220a18c58f755 |
completed | May 2, 2026, 11:54 p.m. |
| NEDg | Description generation | batch_69f68fdd389881909e2132e3ce95d553 |
completed | May 2, 2026, 11:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f69033a66481908bf4ae23fced5983 |
completed | May 3, 2026, midnight |
Created at: April 9, 2026, 5:11 p.m.