Triple

T23560113
Position Surface form Disambiguated ID Type / Status
Subject Badja Djola E579211 entity
Predicate appearedIn P795 FINISHED
Object ER
ER is a long-running American medical drama television series set in a Chicago hospital’s emergency room, 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: [Badja Djola, appearedIn, ER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: ER
Context triple: [Badja Djola, 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
    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: [Badja Djola, appearedIn, ER]
Generated description
ER is a long-running American medical drama television series set in a Chicago hospital’s emergency room, 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’s emergency room, 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_69e245fe24588190888f3aec8407d8e3 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1af672db4819087dbff2c0dfadd7f completed April 29, 2026, 7:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0cdf6bd58c8190af28bb72d950b15d completed May 19, 2026, 10:08 p.m.
NEDg Description generation batch_6a0ce113d3d88190b97af92272a5100f completed May 19, 2026, 10:15 p.m.
NED2 Entity disambiguation (via description) batch_6a0ce187efa48190876f67fef4873af2 completed May 19, 2026, 10:17 p.m.
Created at: April 17, 2026, 6:12 p.m.