Triple
T33739341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loads-a-Money |
E864516
|
entity |
| Predicate | timePeriodSatirized |
P79697
|
FINISHED |
| Object | 1980s |
—
|
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: 1980s | Statement: [Loads-a-Money, timePeriodSatirized, 1980s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodSatirized Context triple: [Loads-a-Money, timePeriodSatirized, 1980s]
-
A.
timePeriodOftenDepicted
Indicates that one entity is a time period that is frequently represented or portrayed in depictions involving the other entity.
-
B.
timePeriod
Indicates the specific span or interval of time during which an event, state, or relationship occurs or is valid.
-
C.
timePeriodFormulated
Indicates the time period during which something (such as a concept, theory, or plan) was formulated or developed.
-
D.
timePeriodOfCensorship
Indicates the span of time during which censorship was in effect for the related entity or content.
-
E.
showsTimePeriod
chosen
Indicates that one entity presents or displays a specific span or interval of time associated with 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_69f3498b24b8819096a65009e521d0e1 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f7c29e1b848190b945c6c6120a5330 |
completed | May 3, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 1, 2026, 1:44 a.m.