Triple

T13005567
Position Surface form Disambiguated ID Type / Status
Subject Lena Younger E322276 entity
Predicate usesMoneyFor P71941 FINISHED
Object down payment on a house in a white neighborhood LITERAL FINISHED

How this triple was built (2 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: down payment on a house in a white neighborhood | Statement: [Lena Younger, usesMoneyFor, down payment on a house in a white neighborhood]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesMoneyFor
Context triple: [Lena Younger, usesMoneyFor, down payment on a house in a white neighborhood]
  • A. incomeUsedFor
    Indicates that some or all of an income amount is allocated or spent for a specified purpose, activity, or recipient.
  • B. expenditureFor chosen
    Indicates a relationship where a specific expenditure is made or allocated for a particular purpose, item, project, or entity.
  • C. usesCurrency
    Indicates that one entity conducts its financial transactions or values using the monetary unit represented by the other entity.
  • D. usedFund
    Indicates that one entity expended or applied a particular fund or financial resource for some purpose.
  • E. hasCost
    Indicates that one entity requires a specified amount of resources (such as money, time, or effort) to be obtained, used, or maintained by another entity.
  • F. None of above.

Provenance (3 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e9b27ec8190815c40a05b9ba7d0 completed April 10, 2026, 10:50 p.m.
PD Predicate disambiguation batch_69d97dc153a081909d13a694993f074a completed April 10, 2026, 10:46 p.m.
Created at: April 9, 2026, 8:48 p.m.