Triple
T17928421
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tessa Berens |
E448259
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Tessa Berens |
—
|
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: Tessa Berens | Statement: [Tessa Berens, name, Tessa Berens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tessa Berens Context triple: [Tessa Berens, name, Tessa Berens]
-
A.
Tessa Berens
chosen
Tessa Berens is a fictional character from the work titled "The Silence."
-
B.
Tessa Humphries
Tessa Humphries is an Australian actress and the daughter of famed comedian and satirist Barry Humphries.
-
C.
Tessa Ross
Tessa Ross is a prominent British film and television producer known for backing acclaimed, often auteur-driven projects across UK cinema and high-end TV drama.
-
D.
Tessa Sanger
Tessa Sanger is the passionate, musically gifted young heroine of Margaret Kennedy’s novel "The Constant Nymph," whose intense, unconventional love and emotional vulnerability drive much of the story’s drama.
-
E.
Melanie Nissen
Melanie Nissen is a music industry figure best known as the co-founder of the influential Los Angeles punk label Slash Records.
- 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_69d8b9f79d14819095540856928f0e25 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4a5505af88190aa7a5cfee0baa3a4 |
completed | April 19, 2026, 9:50 a.m. |
Created at: April 10, 2026, 10:20 a.m.