Triple
T37807123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martin Amis (character) |
E942532
|
entity |
| Predicate | temporalContextOfWork |
P137798
|
FINISHED |
| Object | 1980s British fiction |
—
|
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 British fiction | Statement: [Martin Amis (character), temporalContextOfWork, 1980s British fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temporalContextOfWork Context triple: [Martin Amis (character), temporalContextOfWork, 1980s British fiction]
-
A.
timePeriodOfWorks
chosen
Indicates the span of time during which the associated works were created, produced, or active.
-
B.
hasTemporalOrderInWork
Indicates that one element in a work occurs before or after another element in the temporal sequence of that work.
-
C.
temporalAspect
Indicates the time-related characteristics or phase (such as duration, frequency, or temporal status) associated with an event or relationship.
-
D.
culturalContextOfWork
Indicates the cultural setting, traditions, or background within which a work was created, interpreted, or is meaningfully situated.
-
E.
workWithin
Indicates that one entity performs its activities or duties inside the boundaries, scope, or context defined by another entity.
- 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_69f76ee8104c8190ab17133ccd8f86e6 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd166a488190b1bf9316b0790801 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:19 p.m.