Triple
T18831083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Happy Hour |
E460529
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Hot Mess
Hot Mess is a cocktail commonly served during happy hour, typically featuring a bold, sweet-and-spicy flavor profile.
|
E1345234
|
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: Hot Mess | Statement: [Happy Hour, hasPart, Hot Mess]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hot Mess Context triple: [Happy Hour, hasPart, Hot Mess]
-
A.
What a Mess
"What a Mess" is a song by Yoko Ono from her 1973 avant-garde rock album "Approximately Infinite Universe."
-
B.
I’m a Mess
"I'm a Mess" is a pop song by American singer Bebe Rexha that blends confessional lyrics about emotional turmoil with an upbeat, radio-friendly production.
-
C.
Beautiful Mess
"Beautiful Mess" is a popular country song by American band Diamond Rio, known for its catchy melody and portrayal of love's chaotic charm.
-
D.
I'm a Mess
"I'm a Mess" is a song featured on Anthony Hamilton's album "Comin' from Where I'm From."
-
E.
What-a-Mess
What-a-Mess is a humorous children's book series about a scruffy Afghan Hound puppy whose chaotic misadventures were created by British writer and broadcaster Frank Muir.
- 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: Hot Mess Triple: [Happy Hour, hasPart, Hot Mess]
Generated description
Hot Mess is a cocktail commonly served during happy hour, typically featuring a bold, sweet-and-spicy flavor profile.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hot Mess Target entity description: Hot Mess is a cocktail commonly served during happy hour, typically featuring a bold, sweet-and-spicy flavor profile.
-
A.
What a Mess
"What a Mess" is a song by Yoko Ono from her 1973 avant-garde rock album "Approximately Infinite Universe."
-
B.
I’m a Mess
"I'm a Mess" is a pop song by American singer Bebe Rexha that blends confessional lyrics about emotional turmoil with an upbeat, radio-friendly production.
-
C.
Beautiful Mess
"Beautiful Mess" is a popular country song by American band Diamond Rio, known for its catchy melody and portrayal of love's chaotic charm.
-
D.
I'm a Mess
"I'm a Mess" is a song featured on Anthony Hamilton's album "Comin' from Where I'm From."
-
E.
What-a-Mess
What-a-Mess is a humorous children's book series about a scruffy Afghan Hound puppy whose chaotic misadventures were created by British writer and broadcaster Frank Muir.
- 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a9992bb081908ba517a5c9d93ef3 |
completed | April 20, 2026, 4:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05676782048190810125e6b9317bcd |
completed | May 14, 2026, 6:10 a.m. |
| NEDg | Description generation | batch_6a05692c88c481909a7e321a4975e12f |
completed | May 14, 2026, 6:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0569c79b5c8190a63326c332674dd7 |
completed | May 14, 2026, 6:20 a.m. |
Created at: April 10, 2026, 11:56 a.m.