Triple

T11173444
Position Surface form Disambiguated ID Type / Status
Subject Liz Cooper E264342 entity
Predicate hasLastNameAfterMarriage P14292 FINISHED
Object Cooper E79912 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: Cooper | Statement: [Liz Cooper, hasLastNameAfterMarriage, Cooper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cooper
Context triple: [Liz Cooper, hasLastNameAfterMarriage, Cooper]
  • A. Cooper chosen
    Cooper is a common English surname of occupational origin, traditionally referring to a maker or repairer of wooden casks and barrels.
  • B. Cooper
    Cooper is an electoral district of the Queensland Legislative Assembly that includes suburbs such as Red Hill in Brisbane.
  • C. Cooper
    Cooper is a central character in the science fiction horror film "Event Horizon," serving as a member of the rescue crew sent to investigate the reappearance of the experimental starship.
  • D. Humility Cooper
    Humility Cooper was a young passenger on the Mayflower, traveling as a ward of Edward and Ann Tilley among the early English settlers of Plymouth Colony.
  • E. Coby
    Coby is a given name commonly used as a diminutive or nickname, particularly for names like Jacoba or Jacob.
  • 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: hasLastNameAfterMarriage
Context triple: [Liz Cooper, hasLastNameAfterMarriage, Cooper]
  • A. hasMarriedSurname chosen
    Indicates that a person’s current surname is the one they adopted through marriage.
  • B. hasFamilyNameAfterSecondMarriage
    Indicates that an entity’s family name is the one adopted following their second marriage.
  • C. marriedAfter
    Indicates that one marriage occurred later in time than another specified marriage.
  • D. maidenNameOf
    Indicates that one person’s original family surname before marriage is the maiden name of another person.
  • E. spouseLaterMarriedBy
    Indicates that one’s spouse subsequently entered into a later marriage with another partner.
  • F. None of above.

Provenance (4 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e897774c819088ebc7231cebfba6 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e483816af08190877f86ee52846581 completed April 19, 2026, 7:25 a.m.
PD Predicate disambiguation batch_69d75cf0e6e88190973694abe2990973 completed April 9, 2026, 8:01 a.m.
Created at: April 8, 2026, 9:29 p.m.