Triple
T3694051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellen Brody |
E78411
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object | Sean Brody |
E151434
|
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: Sean Brody | Statement: [Ellen Brody, hasChild, Sean Brody]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sean Brody Context triple: [Ellen Brody, hasChild, Sean Brody]
-
A.
Sean Brody
chosen
Sean Brody is a fictional character from the "Jaws" film series, known as the younger son of police chief Martin Brody.
-
B.
Kevin Brodbin
Kevin Brodbin is a screenwriter known for his work on genre films, including the psychological thriller "Mindhunters."
-
C.
Dennis Burkley
Dennis Burkley was an American character actor known for his burly appearance and roles in numerous film and television productions from the 1970s through the early 2000s.
-
D.
Byron Bowers
Byron Bowers is an American stand-up comedian, writer, and actor known for his work in television, film, and comedy specials.
-
E.
Jim O’Brien
Jim O’Brien is a former American football placekicker best known for kicking the game-winning field goal for the Baltimore Colts in Super Bowl V.
- 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4e9e4748190aa178692ef27e3a6 |
completed | March 8, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b503e201e88190bbac29e6b3722959 |
completed | March 14, 2026, 6:44 a.m. |
Created at: March 8, 2026, 3:26 p.m.