Triple

T4140765
Position Surface form Disambiguated ID Type / Status
Subject West Bengal coast E89265 entity
Predicate hasTown P847 FINISHED
Object Digha
Digha is a popular seaside resort town in the Indian state of West Bengal, known for its long, shallow beaches along the Bay of Bengal.
 E415754 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: Digha | Statement: [West Bengal coast, hasTown, Digha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Digha
Context triple: [West Bengal coast, hasTown, Digha]
  • A. Ghagra
    Ghagra is a traditional long, flared skirt commonly worn by women in parts of South Asia, especially in India and Pakistan, often as part of festive or ceremonial attire.
  • B. Dhundhari
    Dhundhari is an Indo-Aryan language spoken primarily in and around Jaipur and adjoining regions of Rajasthan, India.
  • C. Amethi
    Amethi is a prominent Lok Sabha constituency in Uttar Pradesh, India, long associated with the Nehru–Gandhi political family.
  • D. Trishala
    Trishala is revered in Jain tradition as the mother of Mahavira, the 24th Tirthankara.
  • E. Naraina
    Naraina is a locality in West Delhi, India, known for its mix of residential areas and industrial estates and its location along major city transport routes.
  • 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: Digha
Triple: [West Bengal coast, hasTown, Digha]
Generated description
Digha is a popular seaside resort town in the Indian state of West Bengal, known for its long, shallow beaches along the Bay of Bengal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Digha
Target entity description: Digha is a popular seaside resort town in the Indian state of West Bengal, known for its long, shallow beaches along the Bay of Bengal.
  • A. Ghagra
    Ghagra is a traditional long, flared skirt commonly worn by women in parts of South Asia, especially in India and Pakistan, often as part of festive or ceremonial attire.
  • B. Dhundhari
    Dhundhari is an Indo-Aryan language spoken primarily in and around Jaipur and adjoining regions of Rajasthan, India.
  • C. Amethi
    Amethi is a prominent Lok Sabha constituency in Uttar Pradesh, India, long associated with the Nehru–Gandhi political family.
  • D. Trishala
    Trishala is revered in Jain tradition as the mother of Mahavira, the 24th Tirthankara.
  • E. Naraina
    Naraina is a locality in West Delhi, India, known for its mix of residential areas and industrial estates and its location along major city transport routes.
  • 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_69aed95785788190ae75bcf0cd1cafdf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af0249dd988190bf6826a744e7771f completed March 9, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576ccdf348190a80305485bee354e completed March 14, 2026, 2:55 p.m.
NEDg Description generation batch_69b577785cdc8190ad0864d63aadf908 completed March 14, 2026, 2:58 p.m.
NED2 Entity disambiguation (via description) batch_69b578168ecc8190bc47f0902b130c7d completed March 14, 2026, 3 p.m.
Created at: March 9, 2026, 3:43 p.m.