Triple

T15477082
Position Surface form Disambiguated ID Type / Status
Subject Gilan Province E376809 entity
Predicate hasMajorCity P316 FINISHED
Object Masal
Masal is a small city in northern Iran known for its lush forests, cool climate, and scenic mountainous landscapes in Gilan Province.
 E1159638 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: Masal | Statement: [Gilan Province, hasMajorCity, Masal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Masal
Context triple: [Gilan Province, hasMajorCity, Masal]
  • A. Masaleet
    Masaleet is an alternative transliteration of the Masalit language, a Nilo-Saharan language spoken primarily by the Masalit people in western Sudan and eastern Chad.
  • B. Mashal
    Mashal is the family name of Khaled Mashal, a prominent political leader of the Palestinian organization Hamas.
  • C. Mhasla
    Mhasla is a town in Maharashtra, India, known as a local administrative and commercial center within the coastal Konkan region.
  • D. Masbatenyo
    Masbatenyo is a Central Philippine language spoken primarily on Masbate Island in the Philippines, closely related to Hiligaynon and Cebuano.
  • E. Matsesta
    Matsesta is a spa and resort area near Sochi on Russia’s Black Sea coast, historically renowned for its therapeutic sulfur springs.
  • 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: Masal
Triple: [Gilan Province, hasMajorCity, Masal]
Generated description
Masal is a small city in northern Iran known for its lush forests, cool climate, and scenic mountainous landscapes in Gilan Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Masal
Target entity description: Masal is a small city in northern Iran known for its lush forests, cool climate, and scenic mountainous landscapes in Gilan Province.
  • A. Masaleet
    Masaleet is an alternative transliteration of the Masalit language, a Nilo-Saharan language spoken primarily by the Masalit people in western Sudan and eastern Chad.
  • B. Mashal
    Mashal is the family name of Khaled Mashal, a prominent political leader of the Palestinian organization Hamas.
  • C. Mhasla
    Mhasla is a town in Maharashtra, India, known as a local administrative and commercial center within the coastal Konkan region.
  • D. Masbatenyo
    Masbatenyo is a Central Philippine language spoken primarily on Masbate Island in the Philippines, closely related to Hiligaynon and Cebuano.
  • E. Matsesta
    Matsesta is a spa and resort area near Sochi on Russia’s Black Sea coast, historically renowned for its therapeutic sulfur springs.
  • 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_69d85cd21dcc81908646251b1c26ea00 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f88a5dc8190a2d7830748e29180 completed April 16, 2026, 1:46 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2d0b3e7881908f195701fe222371 completed May 9, 2026, 12:48 p.m.
NEDg Description generation batch_69ff2e4010dc8190b0f81d03acf8ba41 completed May 9, 2026, 12:53 p.m.
NED2 Entity disambiguation (via description) batch_69ff310c2d5c819093295c45307176ec completed May 9, 2026, 1:05 p.m.
Created at: April 10, 2026, 3:34 a.m.