Triple
T17460931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Internet Money |
E425148
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Somebody |
—
|
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: Somebody | Statement: [Internet Money, notableWork, Somebody]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Somebody Context triple: [Internet Money, notableWork, Somebody]
-
A.
Somebody
chosen
"Somebody" is a song featured on the album "The Lover in Me."
-
B.
Somewhere
"Somewhere" is a track by the American rock band Soundgarden from their influential 1991 album *Badmotorfinger*.
-
C.
Somewhere
"Somewhere" is a poignant ballad from the musical West Side Story that expresses a longing for a peaceful place where love can transcend conflict and prejudice.
-
D.
Somewhere
Somewhere is a 2010 introspective drama film written and directed by Sofia Coppola that follows a disaffected Hollywood actor reconnecting with his young daughter.
-
E.
Somewhere
"Somewhere" is a stage play by American playwright Matthew López that explores themes of family, ambition, and the pursuit of dreams against the backdrop of mid-20th-century New York City.
- 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451a3031c8190ab1dd0d41b002dd2 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.