Triple

T2881259
Position Surface form Disambiguated ID Type / Status
Subject Martha Gellhorn E59400 entity
Predicate employer P7 FINISHED
Object The Guardian E39599 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: The Guardian | Statement: [Martha Gellhorn, employer, The Guardian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Guardian
Context triple: [Martha Gellhorn, employer, The Guardian]
  • A. The Guardian chosen
    The Guardian is a British daily newspaper known for its progressive editorial stance and in-depth coverage of national and international news, culture, and opinion.
  • B. The Observer
    The Observer is a long-running British Sunday newspaper known for its in-depth journalism and commentary on politics, culture, and current affairs.
  • C. Scoop
    Scoop is a satirical novel by Evelyn Waugh that lampoons sensationalist journalism and foreign correspondence.
  • D. The Guardian Weekly
    The Guardian Weekly is an international English-language news magazine that compiles and curates key reporting and commentary from The Guardian and its partner publications for a global audience.
  • E. The Gray Lady
    The Gray Lady is a longstanding nickname for The New York Times, reflecting its reputation as a serious, authoritative, and traditional American newspaper.
  • 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_69ab4ac739188190a112f42a5a69c951 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abe0296be081908070bd48fe4fc926 completed March 7, 2026, 8:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69b031633efc819088c2ea29eafaff0f completed March 10, 2026, 2:57 p.m.
Created at: March 6, 2026, 10:03 p.m.