Triple

T7509464
Position Surface form Disambiguated ID Type / Status
Subject Tanzania National Parks Authority E177480 entity
Predicate shortName P43 FINISHED
Object TANAPA
TANAPA is the government agency responsible for managing and conserving Tanzania’s national parks and their wildlife.
 E670233 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: TANAPA | Statement: [Tanzania National Parks Authority, shortName, TANAPA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TANAPA
Context triple: [Tanzania National Parks Authority, shortName, TANAPA]
  • A. TAP
    TAP is a reusable smart fare card system used for paying transit fares across multiple public transportation agencies in the Los Angeles County area.
  • B. TAP
    TAP is the ICAO airline designator for TAP Air Portugal, the flag carrier airline of Portugal.
  • C. PiTaPa
    PiTaPa is a rechargeable contactless smart card system used for fare payment on public transportation networks in the Kansai region of Japan.
  • D. TAI
    TAI is the high-precision time standard used worldwide as the basis for civil timekeeping and scientific measurements.
  • E. TAI
    TAI is the ICAO airline designator assigned to TACA Airlines, a major Central American carrier.
  • 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: TANAPA
Triple: [Tanzania National Parks Authority, shortName, TANAPA]
Generated description
TANAPA is the government agency responsible for managing and conserving Tanzania’s national parks and their wildlife.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TANAPA
Target entity description: TANAPA is the government agency responsible for managing and conserving Tanzania’s national parks and their wildlife.
  • A. TAP
    TAP is the ICAO airline designator for TAP Air Portugal, the flag carrier airline of Portugal.
  • B. TAP
    TAP is a reusable smart fare card system used for paying transit fares across multiple public transportation agencies in the Los Angeles County area.
  • C. PiTaPa
    PiTaPa is a rechargeable contactless smart card system used for fare payment on public transportation networks in the Kansai region of Japan.
  • D. TAI
    TAI is the high-precision time standard used worldwide as the basis for civil timekeeping and scientific measurements.
  • E. TAI
    TAI is the ICAO airline designator assigned to TACA Airlines, a major Central American carrier.
  • 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_69c69f276b108190af2cc790b6554544 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5d052888190ae8678f9134d737c completed March 27, 2026, 9:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8461035b48190ba08c0f759cafe4a completed March 28, 2026, 9:20 p.m.
NEDg Description generation batch_69c84754ec048190be1e37c2189b56ed completed March 28, 2026, 9:25 p.m.
NED2 Entity disambiguation (via description) batch_69c848026e90819098d0b419101f91e1 completed March 28, 2026, 9:28 p.m.
Created at: March 27, 2026, 3:45 p.m.