Triple

T23091056
Position Surface form Disambiguated ID Type / Status
Subject Champ Car World Series E575748 entity
Predicate notableConstructor P44379 FINISHED
Object Lola
Lola is a renowned British racing car constructor best known for designing and building successful single-seater and sports prototype cars used in top international motorsport series.
E1566968 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: Lola | Statement: [Champ Car World Series, notableConstructor, Lola]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lola
Context triple: [Champ Car World Series, notableConstructor, Lola]
  • A. Lola
    Lola is a fictional character portrayed by British actor Chiwetel Ejiofor.
  • B. Lola
    Lola is a 1981 West German drama film directed by Rainer Werner Fassbinder, in which Armin Mueller-Stahl plays a prominent role in a story set in postwar Germany.
  • C. Lola
    "Lola" is a 1970 rock song by The Kinks, famous for its catchy melody and narrative about a romantic encounter that plays with themes of gender identity and ambiguity.
  • D. Lola
    Lola is a lethal, acrobatic henchwoman and primary antagonist in the action film "Transporter 2," known for her distinctive red attire and high-impact fight scenes.
  • E. Lola
    Lola is the seductive, devilish femme fatale character in the musical "Damn Yankees," known for her show-stopping number "Whatever Lola Wants."
  • 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: Lola
Triple: [Champ Car World Series, notableConstructor, Lola]
Generated description
Lola is a renowned British racing car constructor best known for designing and building successful single-seater and sports prototype cars used in top international motorsport series.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lola
Target entity description: Lola is a renowned British racing car constructor best known for designing and building successful single-seater and sports prototype cars used in top international motorsport series.
  • A. Lola chosen
    Lola is a renowned British race car constructor and engineering company known for designing and building competitive chassis for various international motorsport series.
  • B. Lola
    Lola is a character portrayed by actress and filmmaker Alice Englert.
  • C. Lola
    Lola is a feminine given name commonly used in various cultures, often as a diminutive of Dolores or a standalone name.
  • D. Lola
    Lola is a fictional character portrayed by British actor Chiwetel Ejiofor.
  • E. Lola
    Lola is a lethal, acrobatic henchwoman and primary antagonist in the action film "Transporter 2," known for her distinctive red attire and high-impact fight scenes.
  • 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_69e245bf3e3c819086d3448720efc01b completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18da99bec81908ecadf8dab10d1b7 completed April 29, 2026, 4:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c15b77f7c8190b374a581b776d155 completed May 19, 2026, 7:48 a.m.
NEDg Description generation batch_6a0c17791f8481909f0f42f9122e0c3a completed May 19, 2026, 7:55 a.m.
NED2 Entity disambiguation (via description) batch_6a0c1863ea2c81909345cb5701fcd8ed completed May 19, 2026, 7:59 a.m.
Created at: April 17, 2026, 3:57 p.m.