Triple

T570719
Position Surface form Disambiguated ID Type / Status
Subject Charles L. Tiffany E13656 entity
Predicate familyName P18 FINISHED
Object Tiffany E24901 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: Tiffany | Statement: [Charles L. Tiffany, familyName, Tiffany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tiffany
Context triple: [Charles L. Tiffany, familyName, Tiffany]
  • A. Tiffany
    Tiffany is a feminine given name of Greek origin, commonly associated with the feast of Epiphany and used in various English-speaking countries.
  • B. Tiffany & Co. chosen
    Tiffany & Co. is a renowned American luxury jewelry and specialty retailer famous for its diamond engagement rings, sterling silver, and iconic blue boxes.
  • C. Kimberly
    Kimberly is a feminine given name of English origin that has been widely used in the United States since the mid-20th century.
  • D. Blue Nile
    The Blue Nile is a major river in northeastern Africa that flows from Ethiopia into Sudan, forming a principal tributary of the Nile and playing a crucial role in the region’s agriculture and hydroelectric power.
  • E. Tiffany Blue
    Tiffany Blue is the distinctive light robin’s-egg blue color trademarked and famously used by the luxury jewelry brand Tiffany & Co.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b483ac08190b3be152a7cf42011 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4fc8475d881909e80d60fbb50c271 completed March 2, 2026, 2:57 a.m.
Created at: March 1, 2026, 7:33 p.m.