Triple
T12814968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I'm Into Something Good |
E306367
|
entity |
| Predicate | performer |
P1363
|
FINISHED |
| Object | Earl-Jean |
E1005653
|
NE FINISHED |
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: Earl-Jean | Statement: [I'm Into Something Good, performer, Earl-Jean]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Earl-Jean Context triple: [I'm Into Something Good, performer, Earl-Jean]
-
A.
Earl-Jean
chosen
Earl-Jean is an American pop and R&B singer best known for her 1964 solo recording of "I'm Into Something Good," which later became a hit for Herman's Hermits.
-
B.
Bobby Jean
"Bobby Jean" is a rock song by Bruce Springsteen, featured on his 1984 album *Born in the U.S.A.* and often interpreted as a poignant farewell to a close friend or bandmate.
-
C.
Jeanie
Jeanie is a female given name, often used as a diminutive of Jean or Jeanne.
-
D.
Djanet
Djanet is an oasis town in southeastern Algeria, known for its prehistoric rock art, dramatic Sahara landscapes, and role as a gateway to the Tassili n'Ajjer plateau.
-
E.
Laura Jeanne
Laura Jeanne is the birth name of American actress and producer Reese Witherspoon, known for films like "Legally Blonde" and "Walk the Line."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e9beb30819097c256a5aab9a4c8 |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69b97ffd481909c540f52c781f63f |
completed | May 3, 2026, 12:49 a.m. |
Created at: April 9, 2026, 5:31 p.m.