Triple
T31074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inaugural Address "Ask not what your country can do for you" |
E619
|
entity |
| Predicate | quotedIn |
P492
|
FINISHED |
| Object | history textbooks |
—
|
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: history textbooks | Statement: [Inaugural Address "Ask not what your country can do for you", quotedIn, history textbooks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: quotedIn Context triple: [Inaugural Address "Ask not what your country can do for you", quotedIn, history textbooks]
-
A.
notableQuote
chosen
Indicates that one entity is a significant or well-known quotation attributed to, recorded by, or strongly associated with another entity.
-
B.
mentions
Indicates that one entity refers to, cites, or brings up another entity in some form of communication or content.
-
C.
citation
Indicates that one entity references, quotes, or otherwise acknowledges another entity as a source of information or authority.
-
D.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
-
E.
describedIn
Indicates that information about an entity is contained or documented within a specified source, such as a text, document, or media.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a249ec0d288190ac3a0939db61813b |
completed | Feb. 28, 2026, 1:50 a.m. |
| PD | Predicate disambiguation | batch_69a24870417081909c7c01e400c94716 |
completed | Feb. 28, 2026, 1:44 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.