Triple
T2664234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annie Savoy |
E55594
|
entity |
| Predicate | notableQuoteTheme |
P7671
|
FINISHED |
| Object | mixing religion, poetry, and baseball |
—
|
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: mixing religion, poetry, and baseball | Statement: [Annie Savoy, notableQuoteTheme, mixing religion, poetry, and baseball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableQuoteTheme Context triple: [Annie Savoy, notableQuoteTheme, mixing religion, poetry, and baseball]
-
A.
notableQuote
Indicates that one entity is a significant or well-known quotation attributed to, recorded by, or strongly associated with another entity.
-
B.
genreOfQuotes
Indicates that one entity is the literary, thematic, or stylistic genre to which the other entity’s quotes belong.
-
C.
notableTheme
chosen
Indicates that a particular theme is prominently featured in, or strongly associated with, an entity such as a work, event, or body of content.
-
D.
notableQuoteTranslation
Indicates that one quote is a translation of another quote, preserving its meaning across different languages.
-
E.
inspiredByPhrase
Indicates that one entity’s creation, idea, or expression is motivated or shaped by the content or wording of a particular phrase.
- 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_69ab49e54de48190be708cd1cf8be073 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd96dba44819085c3e651afba7806 |
completed | March 7, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69abd81768748190bd965f367cf6ef37 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:54 p.m.