Triple
T18067971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sheena Easton |
E432340
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Sheena |
—
|
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: Sheena | Statement: [Sheena Easton, givenName, Sheena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sheena Context triple: [Sheena Easton, givenName, Sheena]
-
A.
Sheena
Sheena is a 1984 fantasy-adventure film starring Tanya Roberts as a woman raised in the African wilderness who becomes a heroic protector of the jungle.
-
B.
Sheena
chosen
Sheena is the first name of Scottish singer and actress Sheena Easton, known for hits in the 1980s such as "Morning Train (Nine to Five)" and "For Your Eyes Only."
-
C.
Sheena
Sheena is a fictional punk rock girl celebrated in the Ramones’ song “Sheena Is a Punk Rocker,” symbolizing youthful rebellion and the punk subculture.
-
D.
Leeta
Leeta is a Bajoran Dabo girl on Deep Space Nine who becomes a recurring character known for her relationships with several main characters, including Rom.
-
E.
Neela
Neela is a central street racer and love interest in the film "The Fast and the Furious: Tokyo Drift," known for her drifting skills in Tokyo's underground racing scene.
- 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_69d8b9070cac81909fa9473fb1c3f1c7 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4cceb020081909329492591e7b1f2 |
completed | April 19, 2026, 12:39 p.m. |
Created at: April 10, 2026, 10:26 a.m.