Triple
T16673441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goddess of Pop |
E405159
|
entity |
| Predicate | usedFor |
P98
|
FINISHED |
| Object | American actress Cher |
E92362
|
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: American actress Cher | Statement: [Goddess of Pop, usedFor, American actress Cher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: American actress Cher Context triple: [Goddess of Pop, usedFor, American actress Cher]
-
A.
Cher
chosen
Cher is an American singer, actress, and pop culture icon known for her distinctive contralto voice, decades-spanning career, and hits like "Believe" and "If I Could Turn Back Time."
-
B.
Cher
Cher is the four-letter ISO 15924 script code that designates the Cherokee syllabary writing system.
-
C.
Cher
Cher is a department in central France, named after the Cher River and known for its historic towns, vineyards, and agricultural landscapes.
-
D.
Bette Midler
Bette Midler is an American singer, actress, and comedian renowned for her powerful vocals, theatrical performances, and acclaimed work in film, television, and on stage.
-
E.
Marilyn Jeanne Seely
Marilyn Jeanne Seely is an American country music singer and Grand Ole Opry member, best known professionally as Jeannie Seely.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6904008190a79ab30b6d9ccae9 |
completed | April 18, 2026, 12:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0091927a408190a612a9ae2fd30d0a |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 5:19 a.m.