Triple
T33585154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Motors Corporation |
E860258
|
entity |
| Predicate | financialDifficultyPeriod |
P24789
|
FINISHED |
| Object | 1970s |
—
|
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: 1970s | Statement: [American Motors Corporation, financialDifficultyPeriod, 1970s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: financialDifficultyPeriod Context triple: [American Motors Corporation, financialDifficultyPeriod, 1970s]
-
A.
hasEconomicChallenge
chosen
Indicates that an entity is experiencing or facing a financial or economic difficulty, constraint, or problem.
-
B.
hardship
Indicates that an entity is experiencing or causing significant difficulty, suffering, or adverse conditions.
-
C.
debt
Indicates that one entity owes money or an obligation to another entity, typically to be repaid under agreed conditions.
-
D.
financialResponsibility
Indicates that one entity is obligated to bear the costs, debts, or economic consequences associated with another entity or activity.
-
E.
hardshipFeature
Indicates that something possesses a characteristic, condition, or aspect that contributes to or exemplifies hardship.
- 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_69f3497e70e48190951c94d072879bec |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f772d24481908f88edf9b7c0a9e7 |
completed | May 3, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:40 a.m.