Triple
T10719367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Burlesque Lounge |
E252776
|
entity |
| Predicate | hasFinancialProblemInPlot |
P24789
|
FINISHED |
| Object | risk of foreclosure |
—
|
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: risk of foreclosure | Statement: [The Burlesque Lounge, hasFinancialProblemInPlot, risk of foreclosure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFinancialProblemInPlot Context triple: [The Burlesque Lounge, hasFinancialProblemInPlot, risk of foreclosure]
-
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.
hasTragicPast
Indicates that an entity has experienced a significantly sorrowful or traumatic history that influences its present state or characterization.
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6ff3722ec8190b2d78a5630bf6efc |
completed | April 9, 2026, 1:21 a.m. |
| PD | Predicate disambiguation | batch_69d6f30455888190b77f476b8418eaee |
completed | April 9, 2026, 12:29 a.m. |
Created at: April 8, 2026, 9:13 p.m.