Triple

T15809872
Position Surface form Disambiguated ID Type / Status
Subject Vikarabad district E383316 entity
Predicate hasTown P847 FINISHED
Object Parigi
Parigi is a town located in the Vikarabad district of the Indian state of Telangana.
 E1180690 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: Parigi | Statement: [Vikarabad district, hasTown, Parigi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Parigi
Context triple: [Vikarabad district, hasTown, Parigi]
  • A. Parigi
    Parigi is a coastal town that serves as the administrative center of Parigi Moutong Regency in Central Sulawesi, Indonesia.
  • B. Parisi
    Parisi is an Italian surname most notably associated with Giorgio Parisi, a Nobel Prize–winning theoretical physicist known for his work on complex systems and statistical mechanics.
  • C. Parisii
    The Parisii were a Celtic tribe of the Iron Age and Roman period who lived in the area of present-day Paris along the Seine River.
  • D. Paris
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • E. Paris
    Paris is a budget-oriented AMD Sempron processor core designed for entry-level desktop computing.
  • 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: Parigi
Triple: [Vikarabad district, hasTown, Parigi]
Generated description
Parigi is a town located in the Vikarabad district of the Indian state of Telangana.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Parigi
Target entity description: Parigi is a town located in the Vikarabad district of the Indian state of Telangana.
  • A. Parigi
    Parigi is a coastal town that serves as the administrative center of Parigi Moutong Regency in Central Sulawesi, Indonesia.
  • B. Parisi
    Parisi is an Italian surname most notably associated with Giorgio Parisi, a Nobel Prize–winning theoretical physicist known for his work on complex systems and statistical mechanics.
  • C. Parisii
    The Parisii were a Celtic tribe of the Iron Age and Roman period who lived in the area of present-day Paris along the Seine River.
  • D. Paris
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • E. Paris
    Paris is a major Chilean department store and retail chain offering a wide range of apparel, home goods, and consumer products.
  • 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_69d86da2858c819090cc8481e7207b6e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b529c6b481909664153ecc381f7c completed April 16, 2026, 10:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffa131784c8190bd6aba2cca084d20 completed May 9, 2026, 9:03 p.m.
NEDg Description generation batch_69ffa1a919b481909c0007411535588b completed May 9, 2026, 9:05 p.m.
NED2 Entity disambiguation (via description) batch_69ffa4212ca88190973d68dfbd8e103a completed May 9, 2026, 9:16 p.m.
Created at: April 10, 2026, 4:49 a.m.