Triple

T1854080
Position Surface form Disambiguated ID Type / Status
Subject Jessica Rae Springsteen E41661 entity
Predicate hasHorse P13551 FINISHED
Object Vindicat W
Vindicat W is a show jumping horse best known for competing with American equestrian Jessica Springsteen.
E206472 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: Vindicat W | Statement: [Jessica Rae Springsteen, hasHorse, Vindicat W]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vindicat W
Context triple: [Jessica Rae Springsteen, hasHorse, Vindicat W]
  • A. Vence
    Vence is a picturesque hilltop town in the Alpes-Maritimes region of southeastern France, renowned for its medieval old town and its association with modern artists and writers.
  • B. Havoc
    Havoc is an American rapper and record producer best known as one half of the influential hip-hop duo Mobb Deep.
  • C. Scorpion W2
    Scorpion W2 is a modern U.S. Army camouflage pattern designed to provide effective concealment across a wide range of environments.
  • D. Eliminator
    Eliminator is a high-performance, sport-oriented trim package of the Mercury Cougar muscle car, known for its powerful engines and distinctive styling.
  • E. VELO
    VELO is the high-precision vertex detector of the LHCb experiment at CERN, designed to measure particle trajectories very close to the proton–proton collision point.
  • 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: Vindicat W
Triple: [Jessica Rae Springsteen, hasHorse, Vindicat W]
Generated description
Vindicat W is a show jumping horse best known for competing with American equestrian Jessica Springsteen.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vindicat W
Target entity description: Vindicat W is a show jumping horse best known for competing with American equestrian Jessica Springsteen.
  • A. Vence
    Vence is a picturesque hilltop town in the Alpes-Maritimes region of southeastern France, renowned for its medieval old town and its association with modern artists and writers.
  • B. Havoc
    Havoc is an American rapper and record producer best known as one half of the influential hip-hop duo Mobb Deep.
  • C. Scorpion W2
    Scorpion W2 is a modern U.S. Army camouflage pattern designed to provide effective concealment across a wide range of environments.
  • D. Eliminator
    Eliminator is a high-performance, sport-oriented trim package of the Mercury Cougar muscle car, known for its powerful engines and distinctive styling.
  • E. VELO
    VELO is the high-precision vertex detector of the LHCb experiment at CERN, designed to measure particle trajectories very close to the proton–proton collision point.
  • 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_69a8864a83848190a4ec02721306c511 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb7c2354081909ee4da7669932796 completed March 7, 2026, 5:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9c9c6208190a2793994a7f927bd completed March 8, 2026, 7:11 p.m.
NEDg Description generation batch_69adcaf23e748190a031625208f4cf17 completed March 8, 2026, 7:16 p.m.
NED2 Entity disambiguation (via description) batch_69adcbf835b48190aaeb61f34f6aafdc completed March 8, 2026, 7:20 p.m.
Created at: March 4, 2026, 7:33 p.m.