Triple
T15023663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catherine Burks-Brooks |
E378150
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Paul Brooks |
E378150
|
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: Paul Brooks | Statement: [Catherine Burks-Brooks, spouse, Paul Brooks]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Brooks Context triple: [Catherine Burks-Brooks, spouse, Paul Brooks]
-
A.
Paul Brooks
chosen
Paul Brooks is known primarily as the husband of civil rights activist and Freedom Rider Catherine Burks-Brooks.
-
B.
Paul Brooks
Paul Brooks is a British film producer known for his work on popular romantic comedies and genre films, including "The Wedding Date."
-
C.
Rand Brooks
Rand Brooks was an American film and television actor best known for his roles in classic Hollywood productions such as "Gone with the Wind" and numerous Westerns.
-
D.
Eric Brooks
Eric Brooks is the human-vampire hybrid vampire hunter better known as the Marvel Comics character Blade.
-
E.
Golden Brooks
Golden Brooks is an American actress best known for her role as Maya Wilkes on the television sitcom "Girlfriends."
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7de117c8190a1b9fa8d1602057e |
completed | April 15, 2026, 12:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dd499108190b803c6afc0fa00bc |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 10, 2026, 2:56 a.m.