Triple
T2077057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arthur Miller |
E44946
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object | Jane Miller |
E102025
|
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: Jane Miller | Statement: [Arthur Miller, hasChild, Jane Miller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jane Miller Context triple: [Arthur Miller, hasChild, Jane Miller]
-
A.
Jane Miller
chosen
Jane Miller is known as the daughter of renowned American playwright Arthur Miller.
-
B.
Mina Miller
Mina Miller was an American socialite and philanthropist best known as the second wife of inventor Thomas Edison and for her extensive civic and charitable work.
-
C.
Emily Sargent
Emily Sargent was a British artist and watercolorist, best known for her landscapes and for being part of the culturally prominent Sargent family.
-
D.
Freda Miller
Freda Miller is known primarily as the former spouse of American television and radio host Larry King.
-
E.
Mimi Kennedy
Mimi Kennedy is an American actress and author known for her work in film, television, and theater, including roles in series like "Dharma & Greg" and "Mom."
- 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_69a88916c2b48190a5ca2e9b12cad3ed |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abba2fa9c48190958826d5226544df |
completed | March 7, 2026, 5:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae6aea7f58819081790c08791a5841 |
completed | March 9, 2026, 6:38 a.m. |
Created at: March 4, 2026, 7:41 p.m.