Triple
T8653247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rodeo |
E205150
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Hoe-Down |
E409005
|
NE 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: Hoe-Down | Statement: [Rodeo, hasPart, Hoe-Down]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hoe-Down Context triple: [Rodeo, hasPart, Hoe-Down]
-
A.
“Hoe-Down”
chosen
“Hoe-Down” is the lively, folk-inspired final section of Aaron Copland’s ballet *Rodeo*, famous for its use of American cowboy tunes and energetic rhythms.
-
B.
Hoedown
Hoedown is a fast, standards-compliant C library for parsing and rendering Markdown, often used as a core engine in various Markdown processing tools.
-
C.
Mahagonny
Mahagonny is a fictional, hedonistic boomtown created by Bertolt Brecht and Kurt Weill as the setting for their satirical works about capitalism and moral decay.
-
D.
Down by the River
"Down by the River" is a long, guitar-driven rock song by Neil Young and Crazy Horse, noted for its extended jams and dark, ambiguous lyrics.
-
E.
Drinking at the Dam
"Drinking at the Dam" is a melancholic folk song by Smog (Bill Callahan) known for its sparse instrumentation and reflective, narrative lyrics.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca834e56848190abb0eeaec9dedd32 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc484206d881908017897dada63124 |
completed | March 31, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ceccd1d7f88190a5440581325eac63 |
completed | April 2, 2026, 8:08 p.m. |
Created at: March 30, 2026, 6:29 p.m.