Triple

T3635761
Position Surface form Disambiguated ID Type / Status
Subject Stories and Pictures E77061 entity
Predicate alsoKnownAs P39 FINISHED
Object Stories & Pictures E77061 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: Stories & Pictures | Statement: [Stories and Pictures, alsoKnownAs, Stories & Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stories & Pictures
Context triple: [Stories and Pictures, alsoKnownAs, Stories & Pictures]
  • A. Stories and Pictures chosen
    Stories and Pictures is a celebrated collection of Yiddish short stories by I. L. Peretz that helped define modern Jewish literature.
  • B. Stories
    Stories is Snapchat’s signature feature that lets users share photos and videos in a chronological sequence that disappears after 24 hours.
  • C. The Stories
    The Stories is the English translation of the name of Surah Al-Qasas, a chapter of the Qur’an that recounts key narratives of earlier prophets, especially the story of Moses.
  • D. Some Stories
    Some Stories is a collection of short works included within Hannah Arendt’s philosophical study The Human Condition.
  • E. Contes
    Contes is a small commune in southeastern France, located in the Alpes-Maritimes department near Nice on the French Riviera.
  • 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_69ad85dd0be48190b738990cb20c4731 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc325e2548190ae243ae69126e65c completed March 8, 2026, 6:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b44f1ec2bc8190ae88a2010f84e998 completed March 13, 2026, 5:53 p.m.
Created at: March 8, 2026, 3:24 p.m.