Triple

T6967012
Position Surface form Disambiguated ID Type / Status
Subject Graham Jarvis E161513 entity
Predicate appearedInTVSeries P795 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: [Graham Jarvis, appearedInTVSeries, ER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ER
Context triple: [Graham Jarvis, appearedInTVSeries, 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 commonly used abbreviation for United Russia, the dominant ruling political party in the Russian Federation.
  • C. ER
    ER is the vehicle registration code assigned to the German city of Erlangen in the state of Bavaria.
  • 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 two-letter ISO 3166-1 alpha-2 country code assigned to the French overseas department and region of Réunion.
  • 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_69c68853cff881908439d488924a8283 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6db121174819098e73e45f6c9cc91 completed March 27, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69c76195e69c8190a8f7d9ca223a96e6 completed March 28, 2026, 5:05 a.m.
Created at: March 27, 2026, 2:30 p.m.