Triple
T22515624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swan Song Records |
E556638
|
entity |
| Predicate | notableArtist |
P601
|
FINISHED |
| Object |
Sad Café
Sad Café was a British soft rock band best known for their late-1970s hits such as "Every Day Hurts."
|
E1539777
|
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: Sad Café | Statement: [Swan Song Records, notableArtist, Sad Café]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sad Café Context triple: [Swan Song Records, notableArtist, Sad Café]
-
A.
Cafe Au Go Go
Cafe Au Go Go was a famed 1960s Greenwich Village nightclub in New York City known for hosting influential blues, folk, and rock performers.
-
B.
The Cafe
The Cafe is a casual dining spot where people can relax, socialize, and enjoy beverages and light meals.
-
C.
Old Songs in a New Café
Old Songs in a New Café is a collection of essays and reflections by Robert James Waller that blends personal reminiscence, travel writing, and meditations on love and music.
-
D.
From a Sidewalk Cafe
"From a Sidewalk Cafe" is a light, melodic instrumental piece by Canadian pianist and composer Frank Mills, known for its easy-listening charm and romantic, nostalgic mood.
-
E.
The Café Scene
The Café Scene is a painting by French artist Henri Gervex that vividly captures the lively social atmosphere of a Parisian café in the late 19th century.
- 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: Sad Café Triple: [Swan Song Records, notableArtist, Sad Café]
Generated description
Sad Café was a British soft rock band best known for their late-1970s hits such as "Every Day Hurts."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sad Café Target entity description: Sad Café was a British soft rock band best known for their late-1970s hits such as "Every Day Hurts."
-
A.
Cafe Au Go Go
Cafe Au Go Go was a famed 1960s Greenwich Village nightclub in New York City known for hosting influential blues, folk, and rock performers.
-
B.
The Cafe
The Cafe is a casual dining spot where people can relax, socialize, and enjoy beverages and light meals.
-
C.
Old Songs in a New Café
Old Songs in a New Café is a collection of essays and reflections by Robert James Waller that blends personal reminiscence, travel writing, and meditations on love and music.
-
D.
From a Sidewalk Cafe
"From a Sidewalk Cafe" is a light, melodic instrumental piece by Canadian pianist and composer Frank Mills, known for its easy-listening charm and romantic, nostalgic mood.
-
E.
The Café Scene
The Café Scene is a painting by French artist Henri Gervex that vividly captures the lively social atmosphere of a Parisian café in the late 19th century.
- 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_69e11e5657e881909f16ca58352c50da |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15e2cfc908190b3489228a1997f45 |
completed | April 29, 2026, 1:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b17f152848190b4c8dc77596d625d |
completed | May 18, 2026, 1:45 p.m. |
| NEDg | Description generation | batch_6a0b1842c7208190801bce8d6fdb2bca |
completed | May 18, 2026, 1:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b1910f4a8819081644157406c523f |
completed | May 18, 2026, 1:50 p.m. |
Created at: April 16, 2026, 8:50 p.m.