Triple
T10919238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Good Wives |
E257901
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | John Brooke |
E442728
|
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: John Brooke | Statement: [Good Wives, mainCharacter, John Brooke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Brooke Context triple: [Good Wives, mainCharacter, John Brooke]
-
A.
John Brooke
chosen
John Brooke is a fictional character from Louisa May Alcott's classic novel "Little Women," known as the earnest tutor who becomes Meg March's husband.
-
B.
John R. Brooke
John R. Brooke was a United States Army general who served as the first American military governor of Cuba following the Spanish–American War.
-
C.
Philip Holbrook
Philip Holbrook is an individual notable enough to be recognized as a prominent bearer of the surname Holbrook.
-
D.
William Brooks
William Brooks is a person after whom the entity known as Brooks is named, likely due to his notable influence or contributions.
-
E.
Michael Holbrook
Michael Holbrook is a personal name most notably associated with individuals in English-speaking countries, sometimes appearing as a given and family name combination.
- 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77080317881909fc50ac3576cefa8 |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5252da538819091f63ce34709b3b7 |
completed | April 19, 2026, 6:55 p.m. |
Created at: April 8, 2026, 9:22 p.m.