Triple
T17913069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dream |
E447858
|
entity |
| Predicate | loveInterest |
P7325
|
FINISHED |
| Object | Calliope |
—
|
NE NERFINISHED |
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: Calliope | Statement: [Dream, loveInterest, Calliope]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Calliope Context triple: [Dream, loveInterest, Calliope]
-
A.
Calliope
chosen
Calliope is the Muse of epic poetry in Greek mythology, often depicted as the chief of the nine Muses and associated with eloquence and heroic verse.
-
B.
Calliope
Calliope is a small rural town and locality in the Gladstone Region of Queensland, Australia.
-
C.
Calliope Click
Calliope Click is a hip-hop song by American rapper C-Murder, known for its gritty depiction of New Orleans street life and affiliation with the No Limit Records era.
-
D.
Sphinx
Sphinx is a documentation generation tool that converts reStructuredText (and other formats) into HTML, PDF, and other outputs, widely used for Python projects and technical documentation.
-
E.
Sphinx
Sphinx is a taciturn, highly skilled mechanic and member of the car-stealing crew in the film "Gone in 60 Seconds."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9f6d394819082a6d69fd1e23d2f |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a30288ac8190bc633e69447709bf |
completed | April 19, 2026, 9:40 a.m. |
Created at: April 10, 2026, 10:19 a.m.