Triple
T33427667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Register of Historic Places listings in Delaware County, New York |
E856032
|
entity |
| Predicate | isNonFictionTopic |
P24758
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [National Register of Historic Places listings in Delaware County, New York, isNonFictionTopic, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNonFictionTopic Context triple: [National Register of Historic Places listings in Delaware County, New York, isNonFictionTopic, yes]
-
A.
isNonFictionCategory
Indicates that a given category pertains to non-fiction works, such as factual or informational content rather than fictional material.
-
B.
isNonfiction
chosen
Indicates that the work or content is factual rather than fictional, based on real events, people, or information.
-
C.
nonFictionAbout
Indicates that a non-fiction work has content focused on, discusses, or is about a particular subject or entity.
-
D.
hasWrittenNonFiction
Indicates that a person is the author of one or more non-fiction works.
-
E.
includesNotableNonFictionWork
Indicates that a collection, list, or body of work contains at least one notable non-fiction work as a member or component.
- 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_69f349709e7881908c342b4d34f555f4 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70fb4f18c819099ef6d9177b7d205 |
completed | May 3, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:36 a.m.