Triple
T837311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | An Autobiography |
E18096
|
entity |
| Predicate | timeOfNarrativeCoverage |
P11197
|
FINISHED |
| Object | 19th century |
—
|
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: 19th century | Statement: [An Autobiography, timeOfNarrativeCoverage, 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeOfNarrativeCoverage Context triple: [An Autobiography, timeOfNarrativeCoverage, 19th century]
-
A.
timeOfNarrative
chosen
Indicates the specific time or period during which the events of a narrative are set or unfold.
-
B.
timePeriodCoveredTo
Indicates the span or duration of time that is encompassed, addressed, or relevant to a given subject or entity.
-
C.
mediaCoverage
Indicates that one entity reports on, documents, or broadcasts information about another entity through news or media channels.
-
D.
notableEventCoverage
Indicates that there is media or documented coverage specifically focused on a notable event related to the subject.
-
E.
containsNarrativeOf
Indicates that one entity includes or presents the story, account, or narrative content of 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abcf69888190b342363978273ae2 |
completed | March 1, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7dfc5c8190890c9df485d73a86 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.