Triple

T15929319
Position Surface form Disambiguated ID Type / Status
Subject Morang District E386281 entity
Predicate hasMajorTown P316 FINISHED
Object Rangeli
Rangeli is a prominent town in southeastern Nepal that serves as an important local commercial and administrative center in Morang District.
E1184932 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: Rangeli | Statement: [Morang District, hasMajorTown, Rangeli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rangeli
Context triple: [Morang District, hasMajorTown, Rangeli]
  • A. Larimore
    Larimore is a small city in eastern North Dakota, United States, known for its rural character and proximity to Grand Forks.
  • B. Warroad
    Warroad is a small northern Minnesota city near the Canadian border, known for its strong hockey tradition and access to Lake of the Woods.
  • C. Kolda
    Kolda is a regional city in southern Senegal, known as an important administrative and commercial center in the Casamance area.
  • D. Rindal
    Rindal is a small rural municipality and village area in western Norway known for its scenic landscapes and traditional Norwegian countryside character.
  • E. Nylund
    Nylund is a Scandinavian-origin surname most widely recognized through the fictional character Rose Nylund from the television series "The Golden Girls."
  • 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: Rangeli
Triple: [Morang District, hasMajorTown, Rangeli]
Generated description
Rangeli is a prominent town in southeastern Nepal that serves as an important local commercial and administrative center in Morang District.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Rangeli
Target entity description: Rangeli is a prominent town in southeastern Nepal that serves as an important local commercial and administrative center in Morang District.
  • A. Larimore
    Larimore is a small city in eastern North Dakota, United States, known for its rural character and proximity to Grand Forks.
  • B. Warroad
    Warroad is a small northern Minnesota city near the Canadian border, known for its strong hockey tradition and access to Lake of the Woods.
  • C. Kolda
    Kolda is a regional city in southern Senegal, known as an important administrative and commercial center in the Casamance area.
  • D. Rindal
    Rindal is a small rural municipality and village area in western Norway known for its scenic landscapes and traditional Norwegian countryside character.
  • E. Nylund
    Nylund is a Scandinavian-origin surname most widely recognized through the fictional character Rose Nylund from the television series "The Golden Girls."
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156a39abc8190927818f6e185033a completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5b0833081909668c042234b5b75 completed May 9, 2026, 10:31 p.m.
NEDg Description generation batch_69ffb6a526188190be80658fb23cacbd completed May 9, 2026, 10:35 p.m.
NED2 Entity disambiguation (via description) batch_69ffb71cea948190a1c5998654aee8d5 completed May 9, 2026, 10:37 p.m.
Created at: April 10, 2026, 4:52 a.m.