Triple

T9196849
Position Surface form Disambiguated ID Type / Status
Subject Amravati district E220736 entity
Predicate hasTown P847 FINISHED
Object Morshi
Morshi is a town in the Amravati district of Maharashtra, India, known primarily as an agricultural and local trading center.
E784040 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: Morshi | Statement: [Amravati district, hasTown, Morshi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Morshi
Context triple: [Amravati district, hasTown, Morshi]
  • A. Musasir
    Musasir was an ancient Urartian city and religious center in the Armenian Highlands, renowned for its prominent temple dedicated to the god Haldi.
  • B. Shimsha
    Shimsha is a river in southern India that flows through Karnataka and is known for its waterfalls and contribution to the Kaveri river system.
  • C. Moruya
    Moruya is a coastal town in New South Wales, Australia, known for its scenic river setting, nearby beaches, and historic granite quarries.
  • D. Mora
    Mora is a town in central Sweden’s Dalarna region, known for its traditional Swedish culture, proximity to Lake Siljan, and as the finish line of the Vasaloppet cross-country ski race.
  • E. Mora
    Mora is a municipality in Portugal known for its rural Alentejo landscapes, traditional villages, and proximity to the Montargil reservoir.
  • 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: Morshi
Triple: [Amravati district, hasTown, Morshi]
Generated description
Morshi is a town in the Amravati district of Maharashtra, India, known primarily as an agricultural and local trading center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Morshi
Target entity description: Morshi is a town in the Amravati district of Maharashtra, India, known primarily as an agricultural and local trading center.
  • A. Musasir
    Musasir was an ancient Urartian city and religious center in the Armenian Highlands, renowned for its prominent temple dedicated to the god Haldi.
  • B. Shimsha
    Shimsha is a river in southern India that flows through Karnataka and is known for its waterfalls and contribution to the Kaveri river system.
  • C. Moruya
    Moruya is a coastal town in New South Wales, Australia, known for its scenic river setting, nearby beaches, and historic granite quarries.
  • D. Mora
    Mora is a town in central Sweden’s Dalarna region, known for its traditional Swedish culture, proximity to Lake Siljan, and as the finish line of the Vasaloppet cross-country ski race.
  • E. Mora
    Mora is a municipality in Portugal known for its rural Alentejo landscapes, traditional villages, and proximity to the Montargil reservoir.
  • 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_69ca83e7ba70819088b74866d9da2c30 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccd87d6460819097234b5dd3f749b4 completed April 1, 2026, 8:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69d05c3b1af48190bb03af15232c510d completed April 4, 2026, 12:32 a.m.
NEDg Description generation batch_69d05cfb7058819080d80b7f28125199 completed April 4, 2026, 12:36 a.m.
NED2 Entity disambiguation (via description) batch_69d05d91ad4c8190a45db7484b9f058a completed April 4, 2026, 12:38 a.m.
Created at: March 30, 2026, 7:25 p.m.