Triple
T22481871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamasin Day-Lewis |
E555785
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Tamasin |
—
|
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: Tamasin | Statement: [Tamasin Day-Lewis, givenName, Tamasin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tamasin Context triple: [Tamasin Day-Lewis, givenName, Tamasin]
-
A.
Tamasin Barak
Tamasin Barak is a key character in the fantasy novel "Heartstone," set in a world inspired by Jane Austen with dragons and magical warfare.
-
B.
Tamsin
chosen
Tamsin is a feminine given name of English origin, often associated with actresses and public figures such as Tamsin Egerton.
-
C.
Tamara
Tamara is a 2005 supernatural horror film written by Jeffrey Reddick about a bullied high school girl who returns from the dead to exact revenge.
-
D.
Tamara
Tamara is a feminine given name of Hebrew origin, commonly used in various cultures and languages.
-
E.
Damia
Damia is a science fiction novel by Anne McCaffrey, part of her Tower and the Hive series that continues the story of powerful telepaths and their role in human and alien relations.
- 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_69e11e53897c819088863779f8c50bb0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15c397b248190b36c2fbfa6489693 |
completed | April 29, 2026, 1:17 a.m. |
Created at: April 16, 2026, 8:49 p.m.