Triple
T5598452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Rudd |
E147055
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Paul Stephen Rudd |
E147055
|
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 Stephen Rudd | Statement: [Paul Rudd, birthName, Paul Stephen Rudd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Stephen Rudd Context triple: [Paul Rudd, birthName, Paul Stephen Rudd]
-
A.
Paul Rudd
chosen
Paul Rudd is an American actor and comedian best known for his charming, affable roles in films like Clueless, Anchorman, and as the title superhero in Marvel’s Ant-Man series.
-
B.
Magnus Paulin Ferrell
Magnus Paulin Ferrell is the son of Swedish actress Viveca Paulin and American comedian and actor Will Ferrell.
-
C.
Luke Wilson
Luke Wilson is an American actor known for his roles in films such as "The Royal Tenenbaums," "Old School," and "Legally Blonde."
-
D.
Rob Corddry
Rob Corddry is an American actor and comedian best known for his work on "The Daily Show" and in films like "Hot Tub Time Machine."
-
E.
Michael Urie
Michael Urie is an American actor best known for his role as Marc St. James on the television series "Ugly Betty" and for his extensive work in theater and film.
- 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_69c009043d648190a7af89698ccf1e3e |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020d82870819087f9591b5a1021ce |
completed | March 22, 2026, 5:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d3be1bc8190a5cdc1bf694356a6 |
completed | March 22, 2026, 8:12 p.m. |
Created at: March 22, 2026, 3:38 p.m.