Triple

T7860121
Position Surface form Disambiguated ID Type / Status
Subject Jemima Kirke E182472 entity
Predicate twitterUsername P2943 FINISHED
Object jemimakirke
Jemima Kirke is a British-American artist and actress best known for her role as Jessa Johansson on the HBO series "Girls."
 E695781 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: jemimakirke | Statement: [Jemima Kirke, twitterUsername, jemimakirke]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: jemimakirke
Context triple: [Jemima Kirke, twitterUsername, jemimakirke]
  • A. JEK
    JEK is the station code for Jenkintown–Wyncote, a major SEPTA Regional Rail hub in the northern suburbs of Philadelphia.
  • B. Jak
    Jak is the main protagonist of the Jak and Daxter video game series, a heroic adventurer who battles oppressive regimes and dark forces across multiple worlds.
  • C. JEMAD
    JEMAD is the Spanish acronym for the professional head of Spain’s Armed Forces, overseeing their strategic direction and operational command.
  • D. JIM
    JIM is a renowned annual jazz festival held in Marciac, France, known for attracting leading international jazz musicians and enthusiasts.
  • E. JM
    JM is the two-letter ISO 3166-1 alpha-2 country code assigned to Jamaica for international standardization and identification purposes.
  • 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: jemimakirke
Triple: [Jemima Kirke, twitterUsername, jemimakirke]
Generated description
Jemima Kirke is a British-American artist and actress best known for her role as Jessa Johansson on the HBO series "Girls."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: jemimakirke
Target entity description: Jemima Kirke is a British-American artist and actress best known for her role as Jessa Johansson on the HBO series "Girls."
  • A. JEK
    JEK is the station code for Jenkintown–Wyncote, a major SEPTA Regional Rail hub in the northern suburbs of Philadelphia.
  • B. Jak
    Jak is the main protagonist of the Jak and Daxter video game series, a heroic adventurer who battles oppressive regimes and dark forces across multiple worlds.
  • C. JEMAD
    JEMAD is the Spanish acronym for the professional head of Spain’s Armed Forces, overseeing their strategic direction and operational command.
  • D. JIM
    JIM is a renowned annual jazz festival held in Marciac, France, known for attracting leading international jazz musicians and enthusiasts.
  • E. JM
    JM is the two-letter ISO 3166-1 alpha-2 country code assigned to Jamaica for international standardization and identification purposes.
  • F. None of above. chosen

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_69ca82887fd48190975896bf38c4596b completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb36bb6ca4819098bc00739e07cfc8 completed March 31, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5b4138d081908a5ff16b79f0a0c8 completed March 31, 2026, 5:27 a.m.
NEDg Description generation batch_69cb5f1c9ef08190b1b79482f39966c7 completed March 31, 2026, 5:43 a.m.
NED2 Entity disambiguation (via description) batch_69cb767b198481909cfc1f7a44e6f0d8 completed March 31, 2026, 7:23 a.m.
Created at: March 30, 2026, 4:53 p.m.