Triple
T19399858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lesson for Today |
E485291
|
entity |
| Predicate | hasPoeticSpeaker |
P136313
|
FINISHED |
| Object | first-person narrator |
—
|
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: first-person narrator | Statement: [The Lesson for Today, hasPoeticSpeaker, first-person narrator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoeticSpeaker Context triple: [The Lesson for Today, hasPoeticSpeaker, first-person narrator]
-
A.
hasPoeticVoice
Indicates that one entity possesses or exhibits the distinctive poetic style, tone, or expressive voice associated with another entity.
-
B.
hasPoeticLyrics
Indicates that something (such as a song, text, or speech) contains lyrics or wording that are artistic, expressive, or characteristic of poetry.
-
C.
hasPoeticEpigraphs
Indicates that one entity (typically a work) includes poetic epigraphs associated with or prefacing another entity.
-
D.
hasPoeticDevice
Indicates that one entity (typically a text or passage) employs or contains a specific poetic device present in the other entity.
-
E.
hasWittyLyrics
Indicates that the subject contains or is characterized by clever, humorous, or sharply amusing lyrics.
- F. None of above. chosen
Provenance (4 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6257692508190b658928e224d72d7 |
completed | April 20, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69e4fd602f008190aa9bc76ae17e4ce1 |
completed | April 19, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69e50213571881909cd7543a43b51986 |
completed | April 19, 2026, 4:25 p.m. |
Created at: April 10, 2026, 1:36 p.m.