Triple
T1387360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christopher Chaplin |
E29875
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object | Oona O’Neill |
E27480
|
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: Oona O’Neill | Statement: [Christopher Chaplin, mother, Oona O’Neill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oona O’Neill Context triple: [Christopher Chaplin, mother, Oona O’Neill]
-
A.
Oona O’Neill
chosen
Oona O’Neill was an American-born actress and socialite, the daughter of playwright Eugene O’Neill, who became widely known as the longtime wife and muse of filmmaker Charlie Chaplin.
-
B.
Stella Damon
Stella Damon is one of the daughters of American actor and filmmaker Matt Damon.
-
C.
Marianne Gordon
Marianne Gordon is an American actress best known for her film and television work in the 1960s–1980s and for her former marriage to country music star Kenny Rogers.
-
D.
Madelyn Dunham
Madelyn Dunham was the maternal grandmother of Barack Obama and a key figure in his upbringing in Hawaii.
-
E.
Oda Mae Brown
Oda Mae Brown is a comedic, reluctant psychic medium who becomes the key ally in helping a murdered man communicate with his grieving girlfriend in the film "Ghost."
- 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_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c33b6e108190b6b2bca4ddd97b6c |
completed | March 1, 2026, 10:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1596d1c8819081e65469302873ba |
completed | March 8, 2026, 6:22 a.m. |
Created at: March 1, 2026, 7:59 p.m.