Triple
T9665957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Belle Dame sans Merci |
E233703
|
entity |
| Predicate | commonlyAnthologized |
P31760
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [La Belle Dame sans Merci, commonlyAnthologized, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonlyAnthologized Context triple: [La Belle Dame sans Merci, commonlyAnthologized, yes]
-
A.
isFrequentlyAnthologized
chosen
Indicates that a work is often selected and included in multiple anthologies or collected editions.
-
B.
hasLiterarySignificance
Indicates that something holds notable importance, influence, or value within the realm of literature or literary studies.
-
C.
literaryCollection
Indicates that one entity is a collection or compilation of literary works that includes or is associated with the other entity.
-
D.
literaryCenter
Indicates that a location functions as a primary hub or focal point for literary activity, such as writing, publishing, or literary culture.
-
E.
containsPoemsBy
Indicates that one entity (such as a collection or publication) includes poems authored by another entity.
- 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_69ca848d3b6c8190ae98ea554dea58df |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9c38f65c8190a0ed20830249a0f1 |
completed | April 1, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b3239c8190b3ae3b9bd121e4bd |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:14 p.m.