Triple
T140290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gettysburg Address |
E2835
|
entity |
| Predicate | openingWords |
P829
|
FINISHED |
| Object | Four score and seven years ago |
—
|
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: Four score and seven years ago | Statement: [Gettysburg Address, openingWords, Four score and seven years ago]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openingWords Context triple: [Gettysburg Address, openingWords, Four score and seven years ago]
-
A.
openingLine
chosen
Indicates that one entity is the first line or initial statement that begins another entity, such as a text, speech, or conversation.
-
B.
openingTheme
Indicates that one entity serves as the opening theme (such as a song or musical piece) for another entity, typically a show, series, or similar work.
-
C.
opened
Indicates that one entity caused another entity (such as an object, container, or passage) to change from a closed or inaccessible state to an open or accessible state.
-
D.
openedForUse
Indicates that something has been made accessible and available for its intended operation or use.
-
E.
openedIn
Indicates that an entity (such as a business, event, or institution) began operating or was inaugurated in a specific time period or location.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257c679d88190bc71775dab2cfc64 |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a2565426c08190aab68e34a6a2d60e |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.