Triple

T12880590
Position Surface form Disambiguated ID Type / Status
Subject Frank Lane E308081 entity
Predicate hasNickname P39 FINISHED
Object Trader Lane E308081 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: Trader Lane | Statement: [Frank Lane, hasNickname, Trader Lane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trader Lane
Context triple: [Frank Lane, hasNickname, Trader Lane]
  • A. Trader Lane chosen
    Trader Lane was the nickname of Frank Lane, a Major League Baseball executive renowned for his frequent and often bold player trades.
  • B. Trader Sam
    Trader Sam is a whimsical jungle trader character from Disney's Jungle Cruise attraction, known for his humorous bartering and appearances in themed Disney restaurants and lounges.
  • C. Fair Store
    Fair Store was a pioneering Chicago department store building designed by architect William Le Baron Jenney, often associated with the early development of skyscraper architecture.
  • D. Trader Vic
    Trader Vic was a pioneering American restaurateur and tiki bar innovator, best known for popularizing Polynesian-style cocktails and cuisine worldwide.
  • E. Paul the Peddler
    Paul the Peddler is a 19th-century rags-to-riches boys’ novel by Horatio Alger Jr. that follows a poor New York City newsboy striving for success through honesty and hard work.
  • 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970fc1e488190a0c48039f6213e62 completed April 10, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69bba33c081909c0050ff7b868a8e completed May 3, 2026, 12:50 a.m.
Created at: April 9, 2026, 5:39 p.m.