Triple
T10515864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Woman Who Went to Hell, and Other Ballads and Lyrics |
E248027
|
entity |
| Predicate | hasPoemForm |
P83253
|
FINISHED |
| Object | ballad stanza |
—
|
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: ballad stanza | Statement: [The Woman Who Went to Hell, and Other Ballads and Lyrics, hasPoemForm, ballad stanza]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPoemForm Context triple: [The Woman Who Went to Hell, and Other Ballads and Lyrics, hasPoemForm, ballad stanza]
-
A.
hasPoemType
chosen
Indicates that an entity (such as a poem or literary work) is associated with or classified by a specific type or category of poem.
-
B.
containsPoem
Indicates that one entity includes or holds a poem as part of its contents.
-
C.
hasLyricalForm
Indicates that one entity (typically a musical or poetic work) possesses or is characterized by a particular lyrical structure or form.
-
D.
hasPoemSetIn
Indicates that a poem is set in or takes place within a particular location or setting.
-
E.
hasPoeticDevice
Indicates that one entity (typically a text or passage) employs or contains a specific poetic device present in the other 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_69d381c4aa948190942e1d803143fb0e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509cbacb08190a446c864b97823ad |
completed | April 7, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69d4fb919ea08190bcc1193e2014d437 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:28 p.m.