Triple

T12828725
Position Surface form Disambiguated ID Type / Status
Subject Lyari Town E306728 entity
Predicate hasNeighbourhood P4813 FINISHED
Object Daryabad
Daryabad is a residential neighborhood located within Lyari Town in Karachi, Pakistan, known for its dense urban setting and vibrant local community.
E1006707 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: Daryabad | Statement: [Lyari Town, hasNeighbourhood, Daryabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daryabad
Context triple: [Lyari Town, hasNeighbourhood, Daryabad]
  • A. Nazarabad
    Nazarabad is a city in Iran that serves as an important urban center within Alborz Province.
  • B. Astarabad
    Astarabad is the historical name of the city now known as Gorgan in northeastern Iran, once an important regional center near the Caspian Sea.
  • C. Asadabad
    Asadabad is a small but strategically important city in eastern Afghanistan, serving as the capital of Kunar Province near the Pakistani border.
  • D. Asadabad
    Asadabad is a city in western Iran that serves as an administrative and population center within Hamedan Province.
  • E. Nurabad
    Nurabad is a city in western Iran that serves as a local urban center within Lorestan Province.
  • 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: Daryabad
Triple: [Lyari Town, hasNeighbourhood, Daryabad]
Generated description
Daryabad is a residential neighborhood located within Lyari Town in Karachi, Pakistan, known for its dense urban setting and vibrant local community.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Daryabad
Target entity description: Daryabad is a residential neighborhood located within Lyari Town in Karachi, Pakistan, known for its dense urban setting and vibrant local community.
  • A. Nazarabad
    Nazarabad is a city in Iran that serves as an important urban center within Alborz Province.
  • B. Astarabad
    Astarabad is the historical name of the city now known as Gorgan in northeastern Iran, once an important regional center near the Caspian Sea.
  • C. Asadabad
    Asadabad is a small but strategically important city in eastern Afghanistan, serving as the capital of Kunar Province near the Pakistani border.
  • D. Asadabad
    Asadabad is a city in western Iran that serves as an administrative and population center within Hamedan Province.
  • E. Nurabad
    Nurabad is a city in western Iran that serves as a local urban center within Lorestan Province.
  • 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_69d7bdf52b94819096d6f0ba4ab50a98 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96faf9ae481908265e198f917d1e6 completed April 10, 2026, 9:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b99d9bc8190b67f73985c8f6768 completed May 3, 2026, 12:49 a.m.
NEDg Description generation batch_69f69d48e6948190a13afe3b8943d877 completed May 3, 2026, 12:56 a.m.
NED2 Entity disambiguation (via description) batch_69f69dfa2b8481908827025a28bfb056 completed May 3, 2026, 12:59 a.m.
Created at: April 9, 2026, 5:34 p.m.