Triple
T20141002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yes, God, Yes |
E491163
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Alisha Boe |
—
|
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: Alisha Boe | Statement: [Yes, God, Yes, starring, Alisha Boe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alisha Boe Context triple: [Yes, God, Yes, starring, Alisha Boe]
-
A.
Alisha Boe
chosen
Alisha Boe is a Norwegian-American actress best known for her role as Jessica Davis in the Netflix teen drama series "Thirteen Reasons Why."
-
B.
Alisha Newton
Alisha Newton is a Canadian actress best known for playing Georgie Fleming Morris on the long-running family drama series "Heartland."
-
C.
Alisha Woods
Alisha Woods is known as the wife of American professional ice hockey player Zach Parise.
-
D.
Alisha Bailey
Alisha Bailey is an actress known for her role in the action film "Backdraft 2."
-
E.
Alisha Daniels
Alisha Daniels is a central character in the British TV series "Misfits," known for her initially problematic power related to sexual arousal and her complex personal growth throughout the show.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679b179c8190a9511df8ed82098a |
completed | April 20, 2026, 5:51 p.m. |
Created at: April 11, 2026, 11:32 p.m.