Triple
T33961591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hayne–Webster debate |
E870728
|
entity |
| Predicate | significantQuote |
P492
|
FINISHED |
| Object | “Liberty and Union, now and forever, one and inseparable!” |
—
|
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: “Liberty and Union, now and forever, one and inseparable!” | Statement: [Hayne–Webster debate, significantQuote, “Liberty and Union, now and forever, one and inseparable!”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: significantQuote Context triple: [Hayne–Webster debate, significantQuote, “Liberty and Union, now and forever, one and inseparable!”]
-
A.
significantStatement
Indicates that an entity has made a statement or assertion that is considered important, impactful, or highly relevant in a given context.
-
B.
notableQuote
chosen
Indicates that one entity is a significant or well-known quotation attributed to, recorded by, or strongly associated with another entity.
-
C.
memorableQuoteContext
Indicates the situational or narrative context in which a particular memorable quote was spoken or written.
-
D.
quotedWork
Indicates that one entity is a work (e.g., text, speech, or media) that is quoted or cited within another entity.
-
E.
quoteType
Indicates the specific category or classification of a quotation, such as its style, purpose, or contextual role in discourse.
- 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_69f3499ce8e88190b66e1d49ad8c7037 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f78fd5a6388190bfda4bbb2e222e5b |
completed | May 3, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69f78e2ac3fc819081a45c6841375c8d |
completed | May 3, 2026, 6:04 p.m. |
Created at: May 1, 2026, 1:50 a.m.