Triple
T8254903
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cherokee syllabary |
E193047
|
entity |
| Predicate | iso15924Code |
P11937
|
FINISHED |
| Object |
Cher
Cher is the four-letter ISO 15924 script code that designates the Cherokee syllabary writing system.
|
E721079
|
NE FINISHED |
How this triple was built (4 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: Cher | Statement: [Cherokee syllabary, iso15924Code, Cher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cher Context triple: [Cherokee syllabary, iso15924Code, Cher]
-
A.
Cher
Cher is a department in central France, named after the Cher River and known for its historic towns, vineyards, and agricultural landscapes.
-
B.
Cher
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."
-
C.
Barbara West
Barbara West is an actress known for her role in the acclaimed Australian psychological horror film "The Babadook."
-
D.
Cyndi Grecco
Cyndi Grecco is an American singer best known for performing the upbeat 1970s television theme song "Making Our Dreams Come True" from the sitcom Laverne & Shirley.
-
E.
Olivia Newton-John
Olivia Newton-John was a British-Australian singer and actress best known for her role as Sandy in the film musical "Grease" and for hit songs such as "Physical."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Cher Triple: [Cherokee syllabary, iso15924Code, Cher]
Generated description
Cher is the four-letter ISO 15924 script code that designates the Cherokee syllabary writing system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cher Target entity description: Cher is the four-letter ISO 15924 script code that designates the Cherokee syllabary writing system.
-
A.
Cher
Cher is a department in central France, named after the Cher River and known for its historic towns, vineyards, and agricultural landscapes.
-
B.
Cher
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."
-
C.
Barbara West
Barbara West is an actress known for her role in the acclaimed Australian psychological horror film "The Babadook."
-
D.
Cyndi Grecco
Cyndi Grecco is an American singer best known for performing the upbeat 1970s television theme song "Making Our Dreams Come True" from the sitcom Laverne & Shirley.
-
E.
Olivia Newton-John
Olivia Newton-John was a British-Australian singer and actress best known for her role as Sandy in the film musical "Grease" and for hit songs such as "Physical."
- F. None of above. chosen
Provenance (5 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_69ca82dfad9c8190b8cd18fb89f50f40 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78f8eccc8190b43204bf2f8defc1 |
completed | March 31, 2026, 7:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd3553b48881909cc72e443aad9539 |
completed | April 1, 2026, 3:10 p.m. |
| NEDg | Description generation | batch_69cd37a71af481909e82aa29ae558c4a |
completed | April 1, 2026, 3:20 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cd4f0055dc8190803a7c412533aec4 |
completed | April 1, 2026, 4:59 p.m. |
Created at: March 30, 2026, 5:48 p.m.