Triple
T16295841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All the Way (HBO film) |
E395643
|
entity |
| Predicate | portrays |
P264
|
FINISHED |
| Object | Lurleen Wallace |
E60990
|
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: Lurleen Wallace | Statement: [All the Way (HBO film), portrays, Lurleen Wallace]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lurleen Wallace Context triple: [All the Way (HBO film), portrays, Lurleen Wallace]
-
A.
Lurleen Wallace
chosen
Lurleen Wallace was an American politician who became the first female governor of Alabama, serving from 1967 until her death.
-
B.
Ruby Shelby
Ruby Shelby is the young daughter of Thomas Shelby in the British television series "Peaky Blinders."
-
C.
Norma Talmadge
Norma Talmadge was a prominent American silent film actress and producer, renowned in the 1910s and 1920s for her dramatic roles and status as one of Hollywood’s biggest stars.
-
D.
Sandi Marshall
Sandi Marshall is the wife of Bill Marshall.
-
E.
Cynthia Pepper
Cynthia Pepper is an American actress best known for her film and television work in the early 1960s, including a prominent role opposite Elvis Presley.
- 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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e2d08108190bab1b3325923af1d |
completed | April 17, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001f9b42248190a3c8c2647a42aeb9 |
completed | May 10, 2026, 6:03 a.m. |
Created at: April 10, 2026, 5:06 a.m.