Triple

T4196065
Position Surface form Disambiguated ID Type / Status
Subject Katherine E89155 entity
Predicate servedByTrain P6301 FINISHED
Object The Ghan E290594 NE FINISHED

How this triple was built (2 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: The Ghan | Statement: [Katherine, servedByTrain, The Ghan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Ghan
Context triple: [Katherine, servedByTrain, The Ghan]
  • A. The Ghan chosen
    The Ghan is a famous Australian long-distance passenger train that runs through the continent’s interior between Adelaide, Alice Springs, and Darwin.
  • B. Takargo Rail
    Takargo Rail is a Portuguese freight railway company that operates cargo transport services across the national rail network and into neighboring countries.
  • C. Qantas Rising
    Qantas Rising is an autobiographical book by Hudson Fysh recounting the early history and development of Qantas and Australian aviation.
  • D. Serengeti Express
    Serengeti Express is a scenic narrow-gauge railway attraction that transports guests through the African-themed savanna areas of Busch Gardens Tampa Bay.
  • E. Kangaroo Bus
    Kangaroo Bus is a hop-on, hop-off shuttle service that transports visitors around the San Diego Zoo’s main exhibits and attractions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69aed9569a4481908b6c1fcec2a11e21 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af035e87148190a0f0bf48b813ffaa completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b58a0d7fa88190a2c830e298542068 completed March 14, 2026, 4:17 p.m.
Created at: March 9, 2026, 3:46 p.m.