Triple
T13003560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cory Maxson |
E322228
|
entity |
| Predicate | hasMother |
P1909
|
FINISHED |
| Object | Rose Maxson |
E335560
|
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: Rose Maxson | Statement: [Cory Maxson, hasMother, Rose Maxson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rose Maxson Context triple: [Cory Maxson, hasMother, Rose Maxson]
-
A.
Rose Maxson
chosen
Rose Maxson is a central character in the film "Fences," portrayed as a devoted yet resilient wife and mother who anchors her family amid emotional and social turmoil.
-
B.
Leslie Brooks
Leslie Brooks was an American film actress of the 1940s best known for her roles in film noir and crime dramas.
-
C.
Rose Nylund
Rose Nylund is a sweet, naive, and hilariously literal-minded Midwestern woman portrayed by Betty White on the classic sitcom "The Golden Girls."
-
D.
Florence Ryerson
Florence Ryerson was an American screenwriter best known for co-writing the screenplay for the classic 1939 film adaptation of "The Wizard of Oz."
-
E.
Alma Ross
Alma Ross was one of the early wives of famed American jazz and swing musician Louis Prima.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e9a2a448190968833354280e474 |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d3188f88190aafbb1cf97317dc8 |
completed | May 3, 2026, 7:08 p.m. |
Created at: April 9, 2026, 8:47 p.m.