Triple
T29098700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Century Cycle |
E735080
|
entity |
| Predicate | timeSpanNarrative |
P136808
|
FINISHED |
| Object | 1900s to 1990s |
—
|
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: 1900s to 1990s | Statement: [Century Cycle, timeSpanNarrative, 1900s to 1990s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeSpanNarrative Context triple: [Century Cycle, timeSpanNarrative, 1900s to 1990s]
-
A.
timeOfNarrative
Indicates the specific time or period during which the events of a narrative are set or unfold.
-
B.
narrativeTimeSpanHours
Indicates the duration of a narrative or story event measured in hours.
-
C.
timeSpanMentioned
chosen
Indicates that a specific duration or period of time is explicitly referenced in the context.
-
D.
timelineUse
Indicates that one entity utilizes or incorporates another entity within a temporal sequence or schedule (a timeline).
-
E.
timeDescribedAs
Indicates that a specific time or temporal interval is characterized, labeled, or expressed using a particular description or representation.
- 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_69f05b0ed66481908f2e864fa550d2f1 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6618344c08190a3c918a41a871381 |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f65c2376a08190be5215171e908e69 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 11:10 a.m.