Triple

T5489262
Position Surface form Disambiguated ID Type / Status
Subject Heer Ranjha E123659 entity
Predicate mainCharacter P1183 FINISHED
Object Heer E520109 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: Heer | Statement: [Heer Ranjha, mainCharacter, Heer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Heer
Context triple: [Heer Ranjha, mainCharacter, Heer]
  • A. Heer chosen
    Heer is the tragic heroine of the classic Punjabi romantic epic "Heer Ranjha," renowned as a symbol of eternal love and devotion.
  • B. Heer
    The Heer was the land-based component of Nazi Germany’s armed forces, serving as its primary army during World War II.
  • C. Henreid
    Henreid is the surname of Paul Henreid, the Austrian-born actor and director best known for his roles in classic Hollywood films such as "Casablanca" and "Now, Voyager."
  • D. Hein
    Hein is a Dutch surname most notably borne by Piet Hein, a renowned 17th-century naval officer and folk hero of the Dutch Republic.
  • E. Enneüs Heerma
    Enneüs Heerma was a Dutch politician who served as a prominent leader of the Christian Democratic Appeal (CDA) and held several key government positions in the Netherlands.
  • 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_69bd464a2d908190869324ce176779c8 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd927c946c8190aef40679199fede3 completed March 20, 2026, 6:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf488866088190b213bd641f8b247c completed March 22, 2026, 1:40 a.m.
Created at: March 20, 2026, 2:10 p.m.