Triple

T15576873
Position Surface form Disambiguated ID Type / Status
Subject The Card Counter E374391 entity
Predicate featuresCharacter P626 FINISHED
Object Cirk
Cirk is a troubled young man who becomes entangled with the professional gambler protagonist in the 2021 drama film "The Card Counter."
E1164683 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: Cirk | Statement: [The Card Counter, featuresCharacter, Cirk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cirk
Context triple: [The Card Counter, featuresCharacter, Cirk]
  • A. Kruhlaye
    Kruhlaye is a small town in eastern Belarus, located within the Mogilev Region.
  • B. Cerchio
    Cerchio is a small Italian town in the Abruzzo region, known for its location within the mountainous Sirente-Velino area.
  • C. Kolo
    Kolo is an alternative name for the Ewondo language, a Bantu language spoken primarily in Cameroon.
  • D. Kolo
    Kolo is a town in Ogbia Local Government Area of Bayelsa State in Nigeria, known as one of the communities in the Niger Delta region.
  • E. Cincars
    Cincars are an exonym for the Aromanians, a Romance-speaking ethnic group native to the Balkans.
  • 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: Cirk
Triple: [The Card Counter, featuresCharacter, Cirk]
Generated description
Cirk is a troubled young man who becomes entangled with the professional gambler protagonist in the 2021 drama film "The Card Counter."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Cirk
Target entity description: Cirk is a troubled young man who becomes entangled with the professional gambler protagonist in the 2021 drama film "The Card Counter."
  • A. Kruhlaye
    Kruhlaye is a small town in eastern Belarus, located within the Mogilev Region.
  • B. Cerchio
    Cerchio is a small Italian town in the Abruzzo region, known for its location within the mountainous Sirente-Velino area.
  • C. Kolo
    Kolo is an alternative name for the Ewondo language, a Bantu language spoken primarily in Cameroon.
  • D. Kolo
    Kolo is a town in Ogbia Local Government Area of Bayelsa State in Nigeria, known as one of the communities in the Niger Delta region.
  • E. Cincars
    Cincars are an exonym for the Aromanians, a Romance-speaking ethnic group native to the Balkans.
  • 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e22c89081909b1ec0cd36a1ef45 completed April 16, 2026, 2:49 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff4c4978ec8190a57de5d9a2ec6653 completed May 9, 2026, 3:01 p.m.
NEDg Description generation batch_69ff4d0678648190b61fbe79a60da8ec completed May 9, 2026, 3:04 p.m.
NED2 Entity disambiguation (via description) batch_69ff4d9258148190b21201bb09e16999 completed May 9, 2026, 3:06 p.m.
Created at: April 10, 2026, 4:11 a.m.