Triple
T28206187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PoP! |
E717028
|
entity |
| Predicate | activeInFictionalTimeline |
P107311
|
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: [PoP!, activeInFictionalTimeline, 1980s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: activeInFictionalTimeline Context triple: [PoP!, activeInFictionalTimeline, 1980s]
-
A.
activeInFictionalUniverse
Indicates that an entity participates, operates, or has a role within a specified fictional universe or setting.
-
B.
activeInFictionalYear
chosen
Indicates that an entity is active or operating during a specified fictional or imaginary year within a narrative or fictional timeline.
-
C.
isSetInFictionalUniverse
Indicates that a narrative work takes place within a specific fictional universe or setting.
-
D.
hasRealityCounterpartInFiction
Indicates that a fictional element corresponds to or is based on a real-world counterpart within a work of fiction.
-
E.
isContemporaryOfFictionalCharacter
Indicates that one entity exists or occurs in the same fictional time period as another fictional character.
- 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_69efd6b826908190857e6e7dad74ed93 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 27, 2026, 10:35 p.m.