Triple
T1005933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maggie Rogers |
E21710
|
entity |
| Predicate | partOfNarrativePeriod |
P4343
|
FINISHED |
| Object | multiple U.S. presidencies |
—
|
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: multiple U.S. presidencies | Statement: [Maggie Rogers, partOfNarrativePeriod, multiple U.S. presidencies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfNarrativePeriod Context triple: [Maggie Rogers, partOfNarrativePeriod, multiple U.S. presidencies]
-
A.
continuedIntoPeriod
Indicates that an action, state, or relationship that began earlier persisted without interruption into a specified later time period.
-
B.
timeOfNarrative
Indicates the specific time or period during which the events of a narrative are set or unfold.
-
C.
refersToPeriod
chosen
Indicates that one entity designates, references, or is associated with a specific time period or interval.
-
D.
partOfSeriesOfEvents
Indicates that an event is one element within a larger, ordered sequence of related events.
-
E.
occurredDuring
Indicates that one event or action took place within the temporal span of another event or time period.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b51434f081909b301ad1c151af03 |
completed | March 1, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b2e7108190b338b6c19d4aff55 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.