Triple

T7970207
Position Surface form Disambiguated ID Type / Status
Subject Vi Moradi E185302 entity
Predicate hasAlias P455 FINISHED
Object Starling E649568 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: Starling | Statement: [Vi Moradi, hasAlias, Starling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Starling
Context triple: [Vi Moradi, hasAlias, Starling]
  • A. Starling chosen
    Starling is a surname of English origin borne by various notable individuals across fields such as science, politics, and the arts.
  • B. Pidgeon
    Pidgeon is a surname most notably associated with Canadian-American actor Walter Pidgeon, a prominent film star of Hollywood’s classic era.
  • C. Sparrow
    Sparrow is a recurring character in Alison Bechdel’s long-running comic strip "Dykes to Watch Out For," known for her involvement in the strip’s interconnected lesbian and queer community.
  • D. Vogel
    Vogel is a German-origin surname borne by numerous individuals, including figures in sports, arts, science, and public life.
  • E. Vogel
    Vogel is a prominent mountain and ski resort in the Julian Alps of Slovenia, overlooking Lake Bohinj and popular for hiking, skiing, and panoramic views.
  • 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_69ca8297699481909b75a405f01e03af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3bd304dc8190b9feee5e17fc66db completed March 31, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe0aadcc48190ae35154195099029 completed March 31, 2026, 2:56 p.m.
Created at: March 30, 2026, 5:13 p.m.