Triple
T29778557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Class of ’74 |
E755447
|
entity |
| Predicate | fictionalUniverseTime |
P3758
|
FINISHED |
| Object | 1970s United States |
—
|
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 United States | Statement: [Class of ’74, fictionalUniverseTime, 1970s United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalUniverseTime Context triple: [Class of ’74, fictionalUniverseTime, 1970s United States]
-
A.
fictionalTime
Indicates that the associated time or temporal reference exists only within a fictional or imagined context, rather than in real-world chronology.
-
B.
fictionalUniverse
chosen
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
C.
fictionalUniverseEvent
Indicates an event or occurrence that takes place within a specific fictional universe or narrative continuity.
-
D.
fictionalTimeDepth
Indicates a relationship where an entity is associated with a time period or temporal depth that exists only within a fictional or imagined context.
-
E.
existsInFictionalTimePeriod
Indicates that an entity is situated within, or associated with, a time period that is fictional rather than part of real-world history.
- 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_69f0ef878574819088c867fd1a5c8b86 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69fcec5f8b448190b48330a19b462d24 |
completed | May 7, 2026, 7:47 p.m. |
| PD | Predicate disambiguation | batch_69fceaf1e23881908ca24160a638e329 |
completed | May 7, 2026, 7:41 p.m. |
Created at: April 28, 2026, 8:48 p.m.