Triple
T19388791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth McCord |
E485005
|
entity |
| Predicate | hasAdvisor |
P25349
|
FINISHED |
| Object | Blake Moran |
—
|
NE NERFINISHED |
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: Blake Moran | Statement: [Elizabeth McCord, hasAdvisor, Blake Moran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blake Moran Context triple: [Elizabeth McCord, hasAdvisor, Blake Moran]
-
A.
Blake Moran
chosen
Blake Moran is a key fictional aide and policy advisor to the U.S. Secretary of State in the political drama television series "Madam Secretary."
-
B.
Brian Molloy
Brian Molloy is an Irish music industry figure best known as the founder of Dublin’s renowned Windmill Lane Studios, where many iconic recordings have been made.
-
C.
Chris Morley
Chris Morley is a cinematographer best known for his work on the dark fantasy stop-motion film "Mad God."
-
D.
Brian Molony
Brian Molony is a former Canadian bank employee whose notorious embezzlement-fueled gambling addiction became the basis for the film "Owning Mahowny."
-
E.
Michael Bourke
Michael Bourke is a personal name shared by multiple individuals, including various professionals and public figures across different fields.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b425e848190ab5ae8ae0a034fe2 |
completed | April 20, 2026, 12:25 p.m. |
Created at: April 10, 2026, 1:36 p.m.