Triple

T13606048
Position Surface form Disambiguated ID Type / Status
Subject Equity E325063 entity
Predicate setting P1957 FINISHED
Object Wall Street E2854 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: Wall Street | Statement: [Equity, setting, Wall Street]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wall Street
Context triple: [Equity, setting, Wall Street]
  • A. Wall Street chosen
    Wall Street is the historic financial district in Lower Manhattan that serves as a global center for banking, trading, and economic power.
  • B. Wall Street
    Wall Street is a 1987 American drama film directed by Oliver Stone that explores the high-stakes world of corporate finance and greed in New York City.
  • C. 40 Wall Street
    40 Wall Street is a historic neo-Gothic skyscraper in New York City's Financial District, once one of the tallest buildings in the world and later owned and branded by the Trump Organization.
  • D. 14 Wall Street
    14 Wall Street is a historic skyscraper in New York City's Financial District, notable for its distinctive pyramid-shaped roof and its role as a prominent early 20th-century office building.
  • E. Liberty Market
    Liberty Market is a popular commercial and shopping area in Lahore, Pakistan, known for its wide range of clothing, jewelry, and food outlets.
  • 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_69d80769eaf081909d82f44e484d6113 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb07e442c819086a8cbb967c03ad3 completed April 12, 2026, 2:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78ae1d1b08190ad07b159ac3eba4b completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:50 p.m.