Triple

T15625604
Position Surface form Disambiguated ID Type / Status
Subject Mike and Dave Need Wedding Dates E375667 entity
Predicate mainCharacter P1183 FINISHED
Object Tatiana E68776 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: Tatiana | Statement: [Mike and Dave Need Wedding Dates, mainCharacter, Tatiana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tatiana
Context triple: [Mike and Dave Need Wedding Dates, mainCharacter, Tatiana]
  • A. Tatyana chosen
    Tatyana is a feminine given name of Slavic origin, particularly common in Russian-speaking countries.
  • B. Наташа
    Наташа — одна из главных героинь пьесы Максима Горького «На дне», олицетворяющая трагическую судьбу бедной и угнетённой женщины в мире социального дна.
  • C. Irina
    Irina is a feminine given name commonly used in Slavic and other Eastern European cultures, derived from the Greek name Irene meaning "peace."
  • D. Tatiana Nikolaevna
    Tatiana Nikolaevna was the second daughter of Tsar Nicholas II of Russia and a Grand Duchess, remembered as one of the last members of the Romanov imperial family before their execution in 1918.
  • E. Anastasia Shubskaya
    Anastasia Shubskaya is a Russian model and film producer best known as the wife of NHL star Alex Ovechkin.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9e5e248190ae54cda1fde51efb completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f415c2c81909e232e1c6531da93 completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:14 a.m.