Triple
T23191992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love, Marriage & Divorce |
E579766
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Sweat |
—
|
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: Sweat | Statement: [Love, Marriage & Divorce, hasPart, Sweat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sweat Context triple: [Love, Marriage & Divorce, hasPart, Sweat]
-
A.
Sweat
chosen
Sweat is a 2004 studio album by American rapper Nelly that showcases his blend of hip hop and R&B with a more up-tempo, club-oriented sound.
-
B.
Sweat
"Sweat" is a Pulitzer Prize–winning play by Lynn Nottage that explores the lives of working-class friends in a declining Rust Belt town amid deindustrialization and racial tension.
-
C.
Sweat
"Sweat" is a novel by Brazilian writer Jorge Amado, reflecting his early social-realist style and focus on the struggles of the working class.
-
D.
Sweat
Sweat is a musical act known for its association with artist Eddie Scoresazy.
-
E.
Sweat
Sweat is a surname of English origin borne by various individuals, including the American politician and art patron L. D. M. Sweat.
- 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_69e24600eed08190bd7e5295653a1503 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18fd86640819092308751d23c6642 |
completed | April 29, 2026, 4:58 a.m. |
Created at: April 17, 2026, 4:06 p.m.