Triple
T37720097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line-storm |
E939559
|
entity |
| Predicate | hasFictionalContinuity |
P160071
|
FINISHED |
| Object | Future History |
—
|
NE NERFINISHED |
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: Future History | Statement: [Line-storm, hasFictionalContinuity, Future History]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalContinuity Context triple: [Line-storm, hasFictionalContinuity, Future History]
-
A.
hasFictionalSeries
Indicates that one entity is a fictional series that another entity possesses, is associated with, or is the creator/owner of.
-
B.
hasFictionalSuccessor
Indicates that one entity is followed or replaced by another entity within a fictional or narrative context.
-
C.
hasFictionalContent
Indicates that something contains or includes material that is imaginary, invented, or not intended to represent real events or facts.
-
D.
hasFictionalFrame
chosen
Indicates that one entity is presented or interpreted within the context of a fictional narrative, scenario, or imaginative framework provided by another entity.
-
E.
continuesInSequels
Indicates that an element (such as a character, storyline, or theme) persists and appears again in one or more subsequent works in a series.
- 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_69f76edc208c8190bc8b9683f75e1024 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a0076c0a5c4819088b17b95511b93ed |
completed | May 10, 2026, 12:14 p.m. |
| PD | Predicate disambiguation | batch_6a007638a67c81909c091335142260ab |
completed | May 10, 2026, 12:12 p.m. |
Created at: May 3, 2026, 4:18 p.m.