Triple
T18144302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Proudies |
E434343
|
entity |
| Predicate | conflictsWith |
P4897
|
FINISHED |
| Object | Mr. Arabin |
—
|
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: Mr. Arabin | Statement: [The Proudies, conflictsWith, Mr. Arabin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Arabin Context triple: [The Proudies, conflictsWith, Mr. Arabin]
-
A.
Mr. Arabin
chosen
Mr. Arabin is a clergyman and academic who becomes a central romantic interest in Anthony Trollope’s novel "Barchester Towers."
-
B.
Monsieur Ibrahim
Monsieur Ibrahim is a 2003 French drama film in which Omar Sharif delivers an acclaimed performance as a wise Turkish shopkeeper who befriends a lonely Parisian boy.
-
C.
Ahab the Arab
Ahab the Arab is a 1962 novelty song by American singer-comedian Ray Stevens that humorously tells the story of a cartoonish Middle Eastern character.
-
D.
Max Mallowan
Max Mallowan was a prominent British archaeologist, particularly known for his work in the Middle East and for being married to mystery writer Agatha Christie.
-
E.
Mr. Boray
Mr. Boray is a fictional character who appears as a family figure connected to the protagonist Paul Boray in the film "Humoresque."
- 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_69d8b90aac308190801e2c57d8c5bfe5 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de32d3f88190bd9f406729716407 |
completed | April 19, 2026, 1:52 p.m. |
Created at: April 10, 2026, 10:29 a.m.