Triple

T10943809
Position Surface form Disambiguated ID Type / Status
Subject Cress Williams E258541 entity
Predicate appearedIn 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: [Cress Williams, appearedIn, ER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ER
Context triple: [Cress Williams, appearedIn, ER]
  • A. ER
    ER is the zone code for Eastern Railway, one of the major railway zones of Indian Railways headquartered in Kolkata.
  • B. ER
    ER is the abbreviation used to designate the Eastern Region of British Rail, a major administrative division of the former British railway network covering eastern England.
  • C. 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.
  • D. ER
    ER is the vehicle registration code assigned to the German city of Erlangen in the state of Bavaria.
  • E. ER
    ER is the commonly used abbreviation for United Russia, the dominant ruling political party in the Russian Federation.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770c3fb388190a598f89ae59a7b51 completed April 9, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c2dea008190af68336a096b7f7c completed April 17, 2026, 1:57 p.m.
Created at: April 8, 2026, 9:23 p.m.