Triple

T21245394
Position Surface form Disambiguated ID Type / Status
Subject Mahesana district E523593 entity
Predicate hasTown P847 FINISHED
Object Kadi
Kadi is a town in the Mehsana district of Gujarat, India, known for its agricultural markets and growing industrial activities.
 E1472936 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: Kadi | Statement: [Mahesana district, hasTown, Kadi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kadi
Context triple: [Mahesana district, hasTown, Kadi]
  • A. Grand Kadi
    The Grand Kadi is the highest-ranking Islamic judicial authority in a state’s Sharia court system, overseeing the application and interpretation of Islamic law in appellate matters.
  • B. Mawlawiyya
    Mawlawiyya is a Sufi order best known for its whirling dervish ceremonies and spiritual practices inspired by the teachings of the Persian poet and mystic Rumi.
  • C. Fardis
    Fardis is a city in Iran that serves as an urban center within the country's Alborz Province.
  • D. Hedaya
    Hedaya is a surname most notably associated with American character actor Dan Hedaya, known for his numerous film and television roles.
  • E. Muladis
    Muladis were Muslims in medieval Iberia who were originally local Christians that had converted to Islam, often blending Arab-Islamic and Iberian cultural elements.
  • 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: Kadi
Triple: [Mahesana district, hasTown, Kadi]
Generated description
Kadi is a town in the Mehsana district of Gujarat, India, known for its agricultural markets and growing industrial activities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kadi
Target entity description: Kadi is a town in the Mehsana district of Gujarat, India, known for its agricultural markets and growing industrial activities.
  • A. Grand Kadi
    The Grand Kadi is the highest-ranking Islamic judicial authority in a state’s Sharia court system, overseeing the application and interpretation of Islamic law in appellate matters.
  • B. Mawlawiyya
    Mawlawiyya is a Sufi order best known for its whirling dervish ceremonies and spiritual practices inspired by the teachings of the Persian poet and mystic Rumi.
  • C. Fardis
    Fardis is a city in Iran that serves as an urban center within the country's Alborz Province.
  • D. Hedaya
    Hedaya is a surname most notably associated with American character actor Dan Hedaya, known for his numerous film and television roles.
  • E. Muladis
    Muladis were Muslims in medieval Iberia who were originally local Christians that had converted to Islam, often blending Arab-Islamic and Iberian cultural elements.
  • 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_69e0b513b89c81908b27147e91368db2 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73599e5548190ad70d2c2bfa9e919 completed April 21, 2026, 8:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0986f705808190ba3a85d2dacb8818 completed May 17, 2026, 9:14 a.m.
NEDg Description generation batch_6a0988086a648190856057c1327a6ab1 completed May 17, 2026, 9:19 a.m.
NED2 Entity disambiguation (via description) batch_6a0988d4ada081909fe532955b204b94 completed May 17, 2026, 9:22 a.m.
Created at: April 16, 2026, 3:47 p.m.