Triple

T16168646
Position Surface form Disambiguated ID Type / Status
Subject Grant Aleksander E392374 entity
Predicate givenName P17 FINISHED
Object Grant E182443 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: Grant | Statement: [Grant Aleksander, givenName, Grant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grant
Context triple: [Grant Aleksander, givenName, Grant]
  • A. Grant chosen
    Grant is a masculine given name of English origin that is commonly used in the United States and other English-speaking countries.
  • B. Grant
    Grant is a common English-language surname of Scottish origin, borne by numerous notable figures in fields such as politics, entertainment, and sports.
  • C. Grant
    Grant is a publishing company best known for releasing special and limited editions of Stephen King’s works, including volumes in The Dark Tower series.
  • D. Grant Grant
    Grant Grant is a fictional character best known as the parasitically infected antagonist in the horror-comedy film "Slither."
  • E. Sovereign Grant
    The Sovereign Grant is the UK government-funded mechanism that provides the British monarch and royal household with money to support official duties and maintain royal residences.
  • 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_69d87f1d32208190942e4e499a80c18c completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21eb5e6d881908749683091afa90c completed April 17, 2026, 11:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7bb6aac8190a33607abfe9a32d0 completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:02 a.m.