Triple

T8573155
Position Surface form Disambiguated ID Type / Status
Subject Bikaner district E202976 entity
Predicate containsTown P847 FINISHED
Object Lunkaransar
Lunkaransar is a town in the Bikaner district of Rajasthan, India, known for its arid desert landscape and agricultural activities supported by canal irrigation.
 E742520 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: Lunkaransar | Statement: [Bikaner district, containsTown, Lunkaransar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lunkaransar
Context triple: [Bikaner district, containsTown, Lunkaransar]
  • A. Labungkari
    Labungkari is a town in Indonesia’s Southeast Sulawesi province, known as an administrative and local economic center in the region.
  • B. Loarki
    Loarki is a lesser-known dialect of the Rajasthani language spoken by specific communities in the northwestern Indian subcontinent.
  • C. Krakhuna
    Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
  • D. Lakalai
    Lakalai is an Oceanic language spoken by an indigenous community in Papua New Guinea.
  • E. Skeheenarinky
    Skeheenarinky is a small rural village in southern Ireland known for its scenic countryside and traditional community character.
  • 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: Lunkaransar
Triple: [Bikaner district, containsTown, Lunkaransar]
Generated description
Lunkaransar is a town in the Bikaner district of Rajasthan, India, known for its arid desert landscape and agricultural activities supported by canal irrigation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lunkaransar
Target entity description: Lunkaransar is a town in the Bikaner district of Rajasthan, India, known for its arid desert landscape and agricultural activities supported by canal irrigation.
  • A. Labungkari
    Labungkari is a town in Indonesia’s Southeast Sulawesi province, known as an administrative and local economic center in the region.
  • B. Loarki
    Loarki is a lesser-known dialect of the Rajasthani language spoken by specific communities in the northwestern Indian subcontinent.
  • C. Krakhuna
    Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
  • D. Lakalai
    Lakalai is an Oceanic language spoken by an indigenous community in Papua New Guinea.
  • E. Skeheenarinky
    Skeheenarinky is a small rural village in southern Ireland known for its scenic countryside and traditional community character.
  • 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_69ca8328ebe481909a8c038fa79959b4 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbea458c1081908e79bee2cbf97207 completed March 31, 2026, 3:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce898cf8648190b52758b6ecf2959b completed April 2, 2026, 3:21 p.m.
NEDg Description generation batch_69ce8a9df47c81909ba9ef8dff1db7b1 completed April 2, 2026, 3:26 p.m.
NED2 Entity disambiguation (via description) batch_69ce8b48841c8190bcf11aeb25355649 completed April 2, 2026, 3:29 p.m.
Created at: March 30, 2026, 6:21 p.m.