Triple
T16099818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bound for Glory |
E390585
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Gail Strickland |
E454334
|
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: Gail Strickland | Statement: [Bound for Glory, starring, Gail Strickland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gail Strickland Context triple: [Bound for Glory, starring, Gail Strickland]
-
A.
Gail Strickland
chosen
Gail Strickland is an American character actress known for her work in film and television since the 1970s.
-
B.
Gail C. Murphy
Gail C. Murphy is a prominent Canadian computer scientist known for her influential research in software engineering, particularly in improving developer productivity and software evolution.
-
C.
Linda Kay Cooper
Linda Kay Cooper is known as a former spouse of James William Johnson.
-
D.
Maureen Beattie
Maureen Beattie is a Scottish actress known for her extensive work in television, theatre, and film, including roles in British dramas and comedies.
-
E.
Ann Kirkpatrick
Ann Kirkpatrick is an American politician and attorney best known for serving multiple terms as a U.S. Representative from Arizona.
- 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6756948190a7f5ecb375e59701 |
completed | April 17, 2026, 9:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff79a96d08190af69cbb18037f66e |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5 a.m.