Triple
T14886907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larkana District |
E350149
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Larkana city
Larkana city is a major urban center in Sindh, Pakistan, known as the hometown of the Bhutto political family and for its proximity to the ancient Indus Valley site of Mohenjo-daro.
|
E1126122
|
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: Larkana city | Statement: [Larkana District, contains, Larkana city]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Larkana city Context triple: [Larkana District, contains, Larkana city]
-
A.
Haroonabad
Haroonabad is a town in Pakistan known for its agricultural surroundings and role as a local commercial center.
-
B.
Jauharabad
Jauharabad is a planned town in Pakistan’s Punjab province, known for its proximity to key industrial and strategic facilities.
-
C.
Shahabad
Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
-
D.
Wazirabad
Wazirabad is a city in the Gujranwala District of Punjab, Pakistan, known for its cutlery industry and strategic location near the Chenab River.
-
E.
Bhurban
Bhurban is a small, scenic hill resort in Pakistan’s Punjab province, known for its lush forests, cool climate, and popular hotels and golf course.
- 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: Larkana city Triple: [Larkana District, contains, Larkana city]
Generated description
Larkana city is a major urban center in Sindh, Pakistan, known as the hometown of the Bhutto political family and for its proximity to the ancient Indus Valley site of Mohenjo-daro.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Larkana city Target entity description: Larkana city is a major urban center in Sindh, Pakistan, known as the hometown of the Bhutto political family and for its proximity to the ancient Indus Valley site of Mohenjo-daro.
-
A.
Haroonabad
Haroonabad is a town in Pakistan known for its agricultural surroundings and role as a local commercial center.
-
B.
Jauharabad
Jauharabad is a planned town in Pakistan’s Punjab province, known for its proximity to key industrial and strategic facilities.
-
C.
Shahabad
Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
-
D.
Wazirabad
Wazirabad is a city in the Gujranwala District of Punjab, Pakistan, known for its cutlery industry and strategic location near the Chenab River.
-
E.
Bhurban
Bhurban is a small, scenic hill resort in Pakistan’s Punjab province, known for its lush forests, cool climate, and popular hotels and golf course.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5f5b1c88190815f3585770cb135 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b5f22c08190a9530cbd78cfc801 |
completed | May 8, 2026, 11:01 p.m. |
| NEDg | Description generation | batch_69fe6f9b33748190aee0c27879866ca1 |
completed | May 8, 2026, 11:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe703e8c28819081b7bfe638a2202e |
completed | May 8, 2026, 11:22 p.m. |
Created at: April 10, 2026, 1:56 a.m.