Triple
T10171837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heidi Hansen |
E235348
|
entity |
| Predicate | hasFinancialStruggle |
P24789
|
FINISHED |
| Object | works extra shifts to support family |
—
|
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: works extra shifts to support family | Statement: [Heidi Hansen, hasFinancialStruggle, works extra shifts to support family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFinancialStruggle Context triple: [Heidi Hansen, hasFinancialStruggle, works extra shifts to support family]
-
A.
hasEconomicChallenge
chosen
Indicates that an entity is experiencing or facing a financial or economic difficulty, constraint, or problem.
-
B.
hasSocioeconomicIssue
Indicates that an entity is affected by, associated with, or involved in a socioeconomic problem or challenge.
-
C.
hasLessFinancialPowersThan
Indicates that one entity’s authority or capacity to make financial decisions or control financial resources is lower or more limited than that of another entity.
-
D.
debt
Indicates that one entity owes money or an obligation to another entity, typically to be repaid under agreed conditions.
-
E.
hardship
Indicates that an entity is experiencing or causing significant difficulty, suffering, or adverse conditions.
- 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_69ca84ceafd0819085828600e11bed6b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdec9e4e0c819097dceb7bf7757948 |
completed | April 2, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba9956c8190a3e15d091e33149d |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9:10 p.m.