Triple
T15763538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rebecca Gleeson |
E382158
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Eric Bana |
E74991
|
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: Eric Bana | Statement: [Rebecca Gleeson, spouse, Eric Bana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eric Bana Context triple: [Rebecca Gleeson, spouse, Eric Bana]
-
A.
Eric Bana
chosen
Eric Bana is an Australian actor known for his versatile performances in films such as "Hulk," "Munich," and "Troy."
-
B.
Guy Pearce
Guy Pearce is an Australian actor known for his versatile performances in films such as "Memento," "L.A. Confidential," and "The King's Speech."
-
C.
Russell Crowe
Russell Crowe is an Academy Award–winning New Zealand–born actor renowned for intense, transformative performances in films such as Gladiator and A Beautiful Mind.
-
D.
Thomas Roy Skerritt
Thomas Roy Skerritt is an American actor best known for his roles in films such as "M*A*S*H," "Alien," and "Top Gun," as well as the television series "Picket Fences."
-
E.
Josh Brolin
Josh Brolin is an American actor known for his versatile performances in films such as "No Country for Old Men," "W." and for portraying Thanos in the Marvel Cinematic Universe.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b6c9fc8190a1bcf763c4b04b12 |
completed | April 16, 2026, 3 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff8776c2488190ad27fd79e2ce4e14 |
completed | May 9, 2026, 7:13 p.m. |
Created at: April 10, 2026, 4:47 a.m.