Triple

T20454829
Position Surface form Disambiguated ID Type / Status
Subject Greater Sylhet E501747 entity
Predicate majorCity P316 FINISHED
Object Habiganj
Habiganj is a town and district headquarters in northeastern Bangladesh, known for its tea gardens, wetlands, and location within the Sylhet region.
 E1432374 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: Habiganj | Statement: [Greater Sylhet, majorCity, Habiganj]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Habiganj
Context triple: [Greater Sylhet, majorCity, Habiganj]
  • A. Habikino
    Habikino is a city in Osaka Prefecture, Japan, known for its historic kofun burial mounds and role within the Osaka metropolitan area.
  • B. Hatta
    Hatta is an Indonesian surname most prominently associated with Mohammad Hatta, the country’s first vice president and a leading figure in the struggle for independence.
  • C. Hatta
    Hatta is a prominent town in the Damoh district of Madhya Pradesh, India, known as a local commercial and administrative center.
  • D. Gujba
    Gujba is a local government area and town in northeastern Nigeria, known for its predominantly rural communities and location within Yobe State.
  • E. Kahama
    Kahama is a town and district-level administrative center in northwestern Tanzania known for its mining activities and role as a commercial hub in the Shinyanga area.
  • 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: Habiganj
Triple: [Greater Sylhet, majorCity, Habiganj]
Generated description
Habiganj is a town and district headquarters in northeastern Bangladesh, known for its tea gardens, wetlands, and location within the Sylhet region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Habiganj
Target entity description: Habiganj is a town and district headquarters in northeastern Bangladesh, known for its tea gardens, wetlands, and location within the Sylhet region.
  • A. Habikino
    Habikino is a city in Osaka Prefecture, Japan, known for its historic kofun burial mounds and role within the Osaka metropolitan area.
  • B. Hatta
    Hatta is a prominent town in the Damoh district of Madhya Pradesh, India, known as a local commercial and administrative center.
  • C. Hatta
    Hatta is an Indonesian surname most prominently associated with Mohammad Hatta, the country’s first vice president and a leading figure in the struggle for independence.
  • D. Gujba
    Gujba is a local government area and town in northeastern Nigeria, known for its predominantly rural communities and location within Yobe State.
  • E. Kahama
    Kahama is a town and district-level administrative center in northwestern Tanzania known for its mining activities and role as a commercial hub in the Shinyanga area.
  • 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_69e0b4ad4940819098cf2ff6413574e5 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e696a0dd188190ab6cbb387d9c0c1d completed April 20, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a088b0e1d308190abb75555b9d20fd7 completed May 16, 2026, 3:19 p.m.
NEDg Description generation batch_6a088be79cd0819092da701d6d3d2a8a completed May 16, 2026, 3:23 p.m.
NED2 Entity disambiguation (via description) batch_6a088c7e46e48190b890f319ba4f2492 completed May 16, 2026, 3:25 p.m.
Created at: April 16, 2026, 11:32 a.m.