Triple
T19048906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juergen Teller |
E466207
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Teller |
—
|
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: Teller | Statement: [Juergen Teller, familyName, Teller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teller Context triple: [Juergen Teller, familyName, Teller]
-
A.
Teller
chosen
Teller is an American magician, illusionist, and silent half of the duo Penn & Teller, renowned for his innovative, often wordless approach to magic and performance.
-
B.
Teller
Teller is a small coastal city and Native village in western Alaska located on the Seward Peninsula.
-
C.
Kane Teller
Kane Teller is an individual member of the Teller family, a lineage or household identified by the Teller surname.
-
D.
John Dollar
John Dollar is a novel by American author Marianne Wiggins, known for its haunting, literary exploration of colonialism, survival, and power dynamics in the early 20th century.
-
E.
Mr. Franks
Mr. Franks is a music producer best known for his work with the hip-hop collective Legend.
- 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_69d8dd040fb881909af2a964f65ad208 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d8062ea481908cf3fcb790a74956 |
completed | April 20, 2026, 7:38 a.m. |
Created at: April 10, 2026, 12:03 p.m.