Triple
T36162060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autumn in New York |
E1045903
|
entity |
| Predicate | hasBeenWidelyRecordedSince |
P103301
|
FINISHED |
| Object | 1930s |
—
|
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: 1930s | Statement: [Autumn in New York, hasBeenWidelyRecordedSince, 1930s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeenWidelyRecordedSince Context triple: [Autumn in New York, hasBeenWidelyRecordedSince, 1930s]
-
A.
isOftenRecordedOn
Indicates that something is frequently documented, captured, or stored using a particular medium, format, or recording method.
-
B.
historicallyRecordedSince
Indicates that the existence, occurrence, or recognition of one entity has been documented in historical records starting from the time specified by another entity.
-
C.
isFrequentlyRecordedSinceDecade
chosen
Indicates that an entity has been commonly or regularly recorded starting from a specified decade.
-
D.
widelyRecordedIn
Indicates that an event, fact, or phenomenon has been documented or captured in many different records, sources, or media.
-
E.
isFrequentlyRecorded
Indicates that an entity is captured or documented many times within a given dataset, medium, or context.
- 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_69f76e396bc88190b99d221bff9be27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: May 3, 2026, 4:08 p.m.