Triple
T5067766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Birches |
E114184
|
entity |
| Predicate | containsFamousLine |
P12699
|
FINISHED |
| Object | One could do worse than be a swinger of birches. |
—
|
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: One could do worse than be a swinger of birches. | Statement: [Birches, containsFamousLine, One could do worse than be a swinger of birches.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsFamousLine Context triple: [Birches, containsFamousLine, One could do worse than be a swinger of birches.]
-
A.
hasIconicLine
chosen
Indicates that an entity (such as a work or character) is associated with a particularly famous or memorable line of dialogue.
-
B.
hasNotablePhrase
Indicates that an entity is associated with a specific phrase or expression that is considered notable or characteristic of it.
-
C.
hasFamousSignal
Indicates that an entity is associated with a well-known or widely recognized signal, message, or indicator.
-
D.
associatedWithFamousSlogan
Indicates that an entity is connected to, known for, or commonly linked with a particular famous slogan.
-
E.
madeFamousByFilm
Indicates that something became widely known or gained significant public recognition as a result of being featured in a film.
- 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_69bd443cf28c8190ad371d603563dbdd |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd749bf69c819093e75dce56f1c0ab |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd715622b48190a3e8e49a5ef62b4a |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:38 p.m.