Triple

T5731052
Position Surface form Disambiguated ID Type / Status
Subject Kat Dennings E126383 entity
Predicate televisionSeries P3279 FINISHED
Object ER E82125 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: ER | Statement: [Kat Dennings, televisionSeries, ER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ER
Context triple: [Kat Dennings, televisionSeries, ER]
  • A. ER chosen
    ER is a critically acclaimed American medical drama television series that follows the personal and professional lives of staff in a busy Chicago emergency room.
  • B. ER
    ER is the vehicle registration code assigned to the German city of Erlangen in the state of Bavaria.
  • C. ER
    ER is the commonly used abbreviation for United Russia, the dominant ruling political party in the Russian Federation.
  • D. Er
    Er is a minor biblical figure in the Book of Genesis, known as the firstborn son of Judah whose early death led to the levirate marriage of his widow Tamar.
  • E. RE
    RE is the abbreviation for RegioExpress, a category of regional express trains commonly used in European rail transport.
  • 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_69c0083082288190b7478cead6b5430a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c025318d688190bd878c5aa1a28728 completed March 22, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a906e008190bd2b9a3481733f14 completed March 22, 2026, 9:09 p.m.
Created at: March 22, 2026, 3:47 p.m.