Triple
T15905845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Darkest Hour |
E385710
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | M.T. Ahern |
E385710
|
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: M.T. Ahern | Statement: [The Darkest Hour, author, M.T. Ahern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: M.T. Ahern Context triple: [The Darkest Hour, author, M.T. Ahern]
-
A.
M.T. Ahern
chosen
M.T. Ahern is an author best known for writing the work titled "The Darkest Hour."
-
B.
Mary Hartnett
Mary Hartnett is an American lawyer and author best known as a co-author of the definitive biography of U.S. Supreme Court Justice Ruth Bader Ginsburg.
-
C.
Patricia Mangan
Patricia Mangan is a key leader and senior figure at the Irish architectural firm Scott Tallon Walker Architects.
-
D.
Karin Kinsella
Karin Kinsella is the young daughter of Ray Kinsella in the film "Field of Dreams," whose innocent belief in the magical baseball field plays a key emotional role in the story.
-
E.
Anne Mullen
Anne Mullen is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Mullen.
- 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_69d86da686e4819097cbf3b1fc2d881d |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1565956588190ba4726a2879b677d |
completed | April 16, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb0535a808190983b4ff028826cbf |
completed | May 9, 2026, 10:08 p.m. |
Created at: April 10, 2026, 4:52 a.m.