Triple
T15274373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All the News That's Fit to Sing |
E365098
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Automation Song
"Automation Song" is a politically charged folk tune by Phil Ochs that critiques the impact of industrial automation on workers and society.
|
E1146425
|
NE FINISHED |
How this triple was built (4 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: Automation Song | Statement: [All the News That's Fit to Sing, hasPart, Automation Song]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Automation Song Context triple: [All the News That's Fit to Sing, hasPart, Automation Song]
-
A.
Auto-Tune
Auto-Tune is an audio processing technology that automatically corrects or stylizes vocal pitch, widely used in music production for both subtle tuning and distinctive robotic effects.
-
B.
Tune
Tune is the surname of American actor, dancer, singer, theatre director, and choreographer Tommy Tune.
-
C.
Tune
Tune is a historic Viking ship burial site in Norway, notable for yielding one of the earliest known Viking ships, the Tune ship.
-
D.
Music Building
The Music Building is a historic performance and event venue located within Toronto’s Exhibition Place complex.
-
E.
Loop
Loop is an English alternative rock band known for its hypnotic, guitar-driven sound that helped define the late-1980s space rock and noise rock scenes.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Automation Song Triple: [All the News That's Fit to Sing, hasPart, Automation Song]
Generated description
"Automation Song" is a politically charged folk tune by Phil Ochs that critiques the impact of industrial automation on workers and society.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Automation Song Target entity description: "Automation Song" is a politically charged folk tune by Phil Ochs that critiques the impact of industrial automation on workers and society.
-
A.
Auto-Tune
Auto-Tune is an audio processing technology that automatically corrects or stylizes vocal pitch, widely used in music production for both subtle tuning and distinctive robotic effects.
-
B.
Tune
Tune is the surname of American actor, dancer, singer, theatre director, and choreographer Tommy Tune.
-
C.
Tune
Tune is a historic Viking ship burial site in Norway, notable for yielding one of the earliest known Viking ships, the Tune ship.
-
D.
Music Building
The Music Building is a historic performance and event venue located within Toronto’s Exhibition Place complex.
-
E.
Loop
Loop is an English alternative rock band known for its hypnotic, guitar-driven sound that helped define the late-1980s space rock and noise rock scenes.
- F. None of above. chosen
Provenance (5 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00952731c8190bf6a5e6e10c95b94 |
completed | April 15, 2026, 9:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee6069f488190b74793200e5698ff |
completed | May 9, 2026, 7:45 a.m. |
| NEDg | Description generation | batch_69fee82a8ab08190813620457c5357b4 |
completed | May 9, 2026, 7:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fee8cce6c0819084b425b5cd09efe0 |
completed | May 9, 2026, 7:57 a.m. |
Created at: April 10, 2026, 3:14 a.m.