Triple

T12091782
Position Surface form Disambiguated ID Type / Status
Subject Kakinada district E287958 entity
Predicate hasVehicleRegistrationCode P1173 FINISHED
Object AP
AP is the vehicle registration code for the Indian state of Andhra Pradesh.
 E102106 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: AP | Statement: [Kakinada district, hasVehicleRegistrationCode, AP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: AP
Context triple: [Kakinada district, hasVehicleRegistrationCode, AP]
  • A. AP
    AP is a U.S.-based college-level program and exam system for high school students that can earn them advanced placement or credit at many universities.
  • B. AP
    AP is the standard abbreviation for the Pacific Alliance, a Latin American trade bloc focused on economic integration and free movement of goods, services, capital, and people among its member countries.
  • C. AP
    AP is the official two-letter postal abbreviation for the Brazilian state of Amapá.
  • D. AP
    AP is the Associated Press, a major American news agency known for its global news coverage and influential journalism awards.
  • E. AP
    AP is the station code for Antipolo station on Manila’s LRT Line 2 in the Philippines.
  • 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: AP
Triple: [Kakinada district, hasVehicleRegistrationCode, AP]
Generated description
AP is the vehicle registration code for the Indian state of Andhra Pradesh.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: AP
Target entity description: AP is the vehicle registration code for the Indian state of Andhra Pradesh.
  • A. AP chosen
    AP is the official vehicle registration code for the Indian state of Andhra Pradesh.
  • B. AP
    AP is the vehicle registration code used on license plates for vehicles registered in the Argolis regional unit of Greece.
  • C. AP
    AP is the official two-letter postal abbreviation for the Brazilian state of Amapá.
  • D. AP
    AP is the standard abbreviation for the Pacific Alliance, a Latin American trade bloc focused on economic integration and free movement of goods, services, capital, and people among its member countries.
  • E. AP
    AP is the station code for Antipolo station on Manila’s LRT Line 2 in the Philippines.
  • F. None of above.

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_69d6ab4964708190850585628b287b0c completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9151797988190b0d007ea806bcf02 completed April 10, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f66d1b44819091f638d2a621ecde completed May 2, 2026, 1:04 p.m.
NEDg Description generation batch_69f600b6769481909d0308c8f77b2ef3 completed May 2, 2026, 1:48 p.m.
NED2 Entity disambiguation (via description) batch_69f601e7f3b0819098a2245b9f9316b9 completed May 2, 2026, 1:53 p.m.
Created at: April 8, 2026, 9:48 p.m.