Triple
T4108211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosemary Clooney |
E88505
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Clooney |
E85991
|
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: Clooney | Statement: [Rosemary Clooney, familyName, Clooney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clooney Context triple: [Rosemary Clooney, familyName, Clooney]
-
A.
George Clooney
George Clooney is an American actor, filmmaker, and activist renowned for his work in film and television as well as his humanitarian and political advocacy.
-
B.
Alexander Clooney
Alexander Clooney is one of the twin children of human-rights lawyer Amal Clooney and American actor George Clooney.
-
C.
Nick Clooney
chosen
Nick Clooney is an American journalist, television host, and former news anchor known for his long broadcasting career and as the father of actor George Clooney.
-
D.
Dylan Brosnan
Dylan Brosnan is an American model, musician, and filmmaker, best known as one of the sons of actor Pierce Brosnan.
-
E.
Afflecks
Afflecks is an iconic indoor market and alternative shopping emporium in Manchester known for its independent retailers, vintage fashion, and vibrant subcultural atmosphere.
- 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_69aed9484fb881909146f4c772ad277c |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af019e23c481909578eba1c9270282 |
completed | March 9, 2026, 5:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b56b8240248190afd026a450958d4c |
completed | March 14, 2026, 2:06 p.m. |
Created at: March 9, 2026, 3:40 p.m.