Triple
T11903657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winifred Selina Sturt |
E283219
|
entity |
| Predicate | middleName |
P143
|
FINISHED |
| Object | Selina |
E289144
|
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: Selina | Statement: [Winifred Selina Sturt, middleName, Selina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Selina Context triple: [Winifred Selina Sturt, middleName, Selina]
-
A.
Selina
chosen
Selina is a feminine given name of Latin origin, commonly used in English-speaking countries.
-
B.
Selina Rogers
Selina Rogers is the central nightclub singer and performer in the 1943 musical film "Stormy Weather," around whom the story’s romantic and show-business plot revolves.
-
C.
Selina Cadell
Selina Cadell is a British actress and director known for her extensive work in film, television, and theatre, including roles in productions such as "Doc Martin" and "The Lady in the Van."
-
D.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
E.
Barbara
Barbara is a station on Paris Métro Line 4 serving the southern suburbs of the French capital.
- 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_69d6ab2c07e88190ba13b0d21fd6cf33 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8dd1792648190853f15fbf217eebd |
completed | April 10, 2026, 11:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4183d29b081908cfbf4d91a365681 |
completed | May 1, 2026, 3:04 a.m. |
Created at: April 8, 2026, 9:44 p.m.