Triple
T21406750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Dale |
E528054
|
entity |
| Predicate | loveInterestOf |
P7325
|
FINISHED |
| Object | Jack Robin |
—
|
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: Jack Robin | Statement: [Mary Dale, loveInterestOf, Jack Robin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jack Robin Context triple: [Mary Dale, loveInterestOf, Jack Robin]
-
A.
Jack Robin
chosen
Jack Robin is the fictional protagonist of the 1927 film "The Jazz Singer," a young Jewish man torn between his traditional family expectations and his ambition to become a popular jazz performer.
-
B.
Robbin
Robbin is a given name and surname used as a variant of Robbins.
-
C.
Dickie Jones
Dickie Jones was an American child actor best known as the voice of the title character in Disney’s 1940 animated film "Pinocchio."
-
D.
Teddy Lloyd
Teddy Lloyd is a fictional art teacher and former soldier in Muriel Spark’s novel "The Prime of Miss Jean Brodie," whose complex relationship with Jean Brodie and her students drives much of the story’s emotional and moral tension.
-
E.
Jack Dancy
Jack Dancy is the brother of English actor Hugh Dancy and is known primarily for his work outside the entertainment industry, including in travel and publishing.
- 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_69e0b520ee3c8190abddbee7e37e834c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b1b08fdc81909b3ba01add5f6484 |
completed | April 22, 2026, 11:32 a.m. |
Created at: April 16, 2026, 5:32 p.m.