Triple

T15989425
Position Surface form Disambiguated ID Type / Status
Subject Scott Banister E387784 entity
Predicate investedIn P17330 FINISHED
Object Zappos E31209 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: Zappos | Statement: [Scott Banister, investedIn, Zappos]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zappos
Context triple: [Scott Banister, investedIn, Zappos]
  • A. Zappos chosen
    Zappos is a major U.S.-based online retailer best known for its extensive selection of shoes and its customer-centric service culture.
  • B. Jet.com
    Jet.com was an American e-commerce company known for its dynamic pricing model and rapid growth as a Walmart-acquired online retail platform.
  • C. Overstock.com
    Overstock.com is an American online retailer known for selling discounted furniture, home goods, and other merchandise through its e-commerce platform.
  • D. Karl's Shoe Stores
    Karl's Shoe Stores was a prominent American retail shoe chain founded and owned by businessman Harry Karl.
  • E. TOMS Shoes
    TOMS Shoes is a socially conscious footwear and lifestyle brand best known for its one-for-one giving model, donating a pair of shoes to a child in need for every pair purchased.
  • 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_69d86daa562c81908aacc179c0fe8fb5 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e157829ec08190aa4a683e29a0148a completed April 16, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffc3d2369081909efa2d4addf0cf2d completed May 9, 2026, 11:31 p.m.
Created at: April 10, 2026, 4:54 a.m.