Triple

T11844756
Position Surface form Disambiguated ID Type / Status
Subject Professor Marvel E281745 entity
Predicate settingEncounter P101818 FINISHED
Object Kansas E30311 NE FINISHED

How this triple was built (3 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: Kansas | Statement: [Professor Marvel, settingEncounter, Kansas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kansas
Context triple: [Professor Marvel, settingEncounter, Kansas]
  • A. Kansas chosen
    Kansas is a largely rural, landlocked U.S. state known for its extensive plains, agricultural production, and central location within the country.
  • B. Kansas, Georgia
    Kansas, Georgia is a small unincorporated rural community located in Carroll County in the western part of the state.
  • C. Kansas, Alabama
    Kansas, Alabama is a small unincorporated rural community located in Walker County in the U.S. state of Alabama.
  • D. Nebraska
    Nebraska is a landlocked U.S. state on the Great Plains known for its agriculture, prairies, and role as a historic crossroads for westward expansion.
  • E. Nebraska
    Nebraska is a 2013 black-and-white American road comedy-drama film directed by Alexander Payne that follows an aging man's quixotic journey to claim a supposed sweepstakes prize.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: settingEncounter
Context triple: [Professor Marvel, settingEncounter, Kansas]
  • A. setting
    Indicates the place, time, or context in which an event, action, or interaction occurs.
  • B. settingControlled
    Indicates that one entity regulates, adjusts, or determines the configuration or parameters of another entity.
  • C. encountersCharacter
    Indicates that one character comes into contact with or meets another character, typically within a particular situation or context.
  • D. settingOfConflict
    Indicates the location or context in which a conflict between entities takes place.
  • E. settingOfMyth
    Indicates that a location or environment serves as the backdrop or context in which a particular myth takes place.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a65b5ff08190bb58361f6a6acdca completed April 10, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69f1679729c08190a9f6750586f90d8d completed April 29, 2026, 2:06 a.m.
PD Predicate disambiguation batch_69d8a254a57481908a1e6ad97919c416 completed April 10, 2026, 7:10 a.m.
PDg Predicate description generation batch_69d8a43cc0c881909fed7cd759fe90b1 completed April 10, 2026, 7:18 a.m.
Created at: April 8, 2026, 9:43 p.m.