Triple

T21344917
Position Surface form Disambiguated ID Type / Status
Subject David Nutter E526304 entity
Predicate directedEpisodeOf P17519 FINISHED
Object ER
ER is a long-running American medical drama television series set in a Chicago hospital, known for its fast-paced storytelling and ensemble cast.
E82125 NE FINISHED

How this triple was built (4 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: [David Nutter, directedEpisodeOf, ER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ER
Context triple: [David Nutter, directedEpisodeOf, 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
    ER is the standard abbreviation used for the Erie Otters, a junior ice hockey team in the Ontario Hockey League.
  • D. ER
    ER is the two-letter ISO 3166-1 alpha-2 country code for Eritrea, a nation in the Horn of Africa.
  • E. ER
    ER is the ISO 3166-1 alpha-2 country code for Eritrea, a nation in the Horn of Africa.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: ER
Triple: [David Nutter, directedEpisodeOf, ER]
Generated description
ER is a long-running American medical drama television series set in a Chicago hospital, known for its fast-paced storytelling and ensemble cast.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: ER
Target entity description: ER is a long-running American medical drama television series set in a Chicago hospital, known for its fast-paced storytelling and ensemble cast.
  • 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 standard abbreviation used for the Erie Otters, a junior ice hockey team in the Ontario Hockey League.
  • C. ER
    ER is the commonly used abbreviation for United Russia, the dominant ruling political party in the Russian Federation.
  • D. ER
    ER is the station code for Ermita station, a stop on Manila’s Light Rail Transit system in the Philippines.
  • E. 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.
  • F. None of above.

Provenance (5 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_69e0b51c33048190ab27cede74ef798c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e8a853e50c81909f8854eadf053049 completed April 22, 2026, 10:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09a5c8c9808190810982de97320df3 completed May 17, 2026, 11:26 a.m.
NEDg Description generation batch_6a09a6848c1c8190992ae7cdfeabdcf8 completed May 17, 2026, 11:29 a.m.
NED2 Entity disambiguation (via description) batch_6a09aae23f2c81908f08d290277e22f9 completed May 17, 2026, 11:47 a.m.
Created at: April 16, 2026, 4:53 p.m.