Triple

T5907721
Position Surface form Disambiguated ID Type / Status
Subject Ted Tally E131382 entity
Predicate familyName P18 FINISHED
Object Tally E55396 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: Tally | Statement: [Ted Tally, familyName, Tally]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tally
Context triple: [Ted Tally, familyName, Tally]
  • A. Tally chosen
    Tally is a common nickname for Tallahassee, the capital city of the U.S. state of Florida.
  • B. Tetro
    Tetro is a 2009 drama film directed by Francis Ford Coppola, in which Maribel Verdú plays a key supporting role in a story about fractured family relationships and artistic rivalry in Buenos Aires.
  • C. Count Them In
    Count Them In is a Royal British Legion campaign aimed at improving recognition and support for the UK Armed Forces community, particularly through better data collection and representation.
  • D. Tikkana
    Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
  • E. Count of Mark
    Count of Mark was a historic noble title associated with the County of Mark in the Holy Roman Empire, often held by rulers who also governed larger German principalities such as Brandenburg and Prussia.
  • 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_69c008593a44819081a07ae0efe6c574 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03772d9dc8190899fe49ef887e685 completed March 22, 2026, 6:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0b16f568081908839cd2403b7534c completed March 23, 2026, 3:20 a.m.
Created at: March 22, 2026, 3:59 p.m.