Triple

T6734785
Position Surface form Disambiguated ID Type / Status
Subject Dhar E153725 entity
Predicate hasBuilding P105 FINISHED
Object Lath Masjid
Lath Masjid is a historic mosque in Dhar, India, notable for incorporating an ancient iron pillar into its architecture.
 E615168 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: Lath Masjid | Statement: [Dhar, hasBuilding, Lath Masjid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lath Masjid
Context triple: [Dhar, hasBuilding, Lath Masjid]
  • A. موتی مسجد
    موتی مسجد ایک تاریخی سفید سنگ مرمر کی مسجد ہے جو دہلی کے لال قلعہ کے اندر مغل دور میں تعمیر کی گئی تھی۔
  • B. Taluksangay Mosque
    Taluksangay Mosque is a historic Islamic place of worship in Zamboanga City, Philippines, known as one of the oldest and most significant mosques in the region.
  • C. मोती मस्जिद
    मोती मस्जिद दिल्ली के लाल किले परिसर में स्थित सफेद संगमरमर से बनी एक ऐतिहासिक और सुंदर मुगलकालीन मस्जिद है।
  • D. Kevada Masjid
    Kevada Masjid is a historic 15th-century mosque in Champaner, Gujarat, India, noted for its elegant stone architecture, intricate carvings, and integration of garden and water features.
  • E. Nagina Masjid
    Nagina Masjid is a finely carved 15th-century mosque at Champaner in Gujarat, India, renowned for its elegant stone architecture and intricate ornamentation.
  • 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: Lath Masjid
Triple: [Dhar, hasBuilding, Lath Masjid]
Generated description
Lath Masjid is a historic mosque in Dhar, India, notable for incorporating an ancient iron pillar into its architecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lath Masjid
Target entity description: Lath Masjid is a historic mosque in Dhar, India, notable for incorporating an ancient iron pillar into its architecture.
  • A. موتی مسجد
    موتی مسجد ایک تاریخی سفید سنگ مرمر کی مسجد ہے جو دہلی کے لال قلعہ کے اندر مغل دور میں تعمیر کی گئی تھی۔
  • B. Taluksangay Mosque
    Taluksangay Mosque is a historic Islamic place of worship in Zamboanga City, Philippines, known as one of the oldest and most significant mosques in the region.
  • C. मोती मस्जिद
    मोती मस्जिद दिल्ली के लाल किले परिसर में स्थित सफेद संगमरमर से बनी एक ऐतिहासिक और सुंदर मुगलकालीन मस्जिद है।
  • D. Kevada Masjid
    Kevada Masjid is a historic 15th-century mosque in Champaner, Gujarat, India, noted for its elegant stone architecture, intricate carvings, and integration of garden and water features.
  • E. Nagina Masjid
    Nagina Masjid is a finely carved 15th-century mosque at Champaner in Gujarat, India, renowned for its elegant stone architecture and intricate ornamentation.
  • 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_69c6880bdd68819097de8b6099992682 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d16ecbe08190b019d547f631a725 completed March 27, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70b0703288190906cfcaba9d9c85a completed March 27, 2026, 10:56 p.m.
NEDg Description generation batch_69c70bffe7b48190bbe217bc9fbb08ab completed March 27, 2026, 11 p.m.
NED2 Entity disambiguation (via description) batch_69c70c84de7081908d86c6f710410443 completed March 27, 2026, 11:02 p.m.
Created at: March 27, 2026, 2:09 p.m.