Triple
T609167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boston University |
E12058
|
entity |
| Predicate | hasNotableAlumni |
P51
|
FINISHED |
| Object | Geena Davis |
E75895
|
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: Geena Davis | Statement: [Boston University, hasNotableAlumni, Geena Davis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geena Davis Context triple: [Boston University, hasNotableAlumni, Geena Davis]
-
A.
Geena Davis
chosen
Geena Davis is an American actress and producer known for her roles in films such as "Thelma & Louise," "A League of Their Own," and "The Fly," as well as for her advocacy for gender equality in media.
-
B.
Daryl Hannah
Daryl Hannah is an American actress best known for her roles in films such as "Splash," "Blade Runner," and "Kill Bill."
-
C.
Susan Sarandon
Susan Sarandon is an acclaimed American actress known for her versatile performances in film and television, including her Academy Award–winning role in "Dead Man Walking."
-
D.
Tyne Daly
Tyne Daly is an American actress acclaimed for her powerful performances in television dramas, film, and theater, including her iconic role in the series "Cagney & Lacey."
-
E.
Gina Gershon
Gina Gershon is an American actress known for her versatile roles in film, television, and theater, including standout performances in movies like "Bound" and "Showgirls."
- 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df54eec8190af3f5f04c01d5d2a |
completed | March 1, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5740161cc81909a0086f7c541be98 |
completed | March 2, 2026, 11:26 a.m. |
Created at: March 1, 2026, 7:35 p.m.