Triple
T16585275
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Hawkes |
E402939
|
entity |
| Predicate | portrayedCharacter |
P1668
|
FINISHED |
| Object | Mark O'Brien |
E1094891
|
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: Mark O'Brien | Statement: [John Hawkes, portrayedCharacter, Mark O'Brien]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark O'Brien Context triple: [John Hawkes, portrayedCharacter, Mark O'Brien]
-
A.
Mark O'Brien
Mark O'Brien is an American actor best known for his roles in television series such as City on a Hill and Halt and Catch Fire, as well as various film and independent projects.
-
B.
Mark O'Brien
chosen
Mark O'Brien is a Canadian actor, writer, and director known for his work in film and television, including writing the screenplay for the film "The Righteous."
-
C.
Mark O’Brien
Mark O’Brien is an American local politician who has served as the mayor of Augusta, Maine.
-
D.
Stephen Gleason
Stephen Gleason is an individual notable enough to be specifically distinguished as a bearer of the surname Gleason.
-
E.
Daniel Lavoie
Daniel Lavoie is a Canadian singer-songwriter, actor, and composer known for his successful music career and his prominent role in the musical "Notre-Dame de Paris."
- 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_69d88387363c8190a97a0c942130de97 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3599b057881909fcb8bbb156633a8 |
completed | April 18, 2026, 10:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006ef4f17c819095b3c6f8644b687b |
completed | May 10, 2026, 11:41 a.m. |
Created at: April 10, 2026, 5:16 a.m.