Triple
T22877129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Grind Date |
E567353
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Much More |
—
|
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: Much More | Statement: [The Grind Date, hasPart, Much More]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Much More Context triple: [The Grind Date, hasPart, Much More]
-
A.
Much More
chosen
"Much More" is a reflective and wistful song from the long-running Off-Broadway musical *The Fantasticks*, sung by the character Luisa as she dreams of a life filled with adventure and romance beyond her small world.
-
B.
Way More
"Way More" is a track by Chicago rapper Lil Durk featured on his mixtape "Signed to the Streets 3."
-
C.
Please, No More
"Please, No More" is a song featured on the album "Let's Roll."
-
D.
How Much More
"How Much More" is a song by the American rock band The Go-Go's from their influential 1981 debut album "Beauty and the Beat."
-
E.
What More Do You Want
"What More Do You Want" is a song featured on the album *Some Lessons Learned* by Kristin Chenoweth.
- 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_69e24589d8348190b96422d13a678bc1 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17f5966c08190a9ded9b19b166112 |
completed | April 29, 2026, 3:47 a.m. |
Created at: April 17, 2026, 3:39 p.m.