Triple
T14067358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phyllis Coates |
E338509
|
entity |
| Predicate | stageName |
P7872
|
FINISHED |
| Object | Phyllis Coates |
E338509
|
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: Phyllis Coates | Statement: [Phyllis Coates, stageName, Phyllis Coates]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Phyllis Coates Context triple: [Phyllis Coates, stageName, Phyllis Coates]
-
A.
Phyllis Coates
chosen
Phyllis Coates is an American actress best known for playing Lois Lane in the early 1950s Superman film and television adaptations.
-
B.
Phyllis Loughton
Phyllis Loughton was an American actress and acting teacher best known for her work on stage and for her marriage to filmmaker George Seaton.
-
C.
Phyllis Garr
Phyllis Garr is the mother of American actress and comedian Teri Garr.
-
D.
Phyllis Carlyle
Phyllis Carlyle was a film producer best known for her work on influential 1990s movies, including the psychological thriller "Seven."
-
E.
Phyllis Crane
Phyllis Crane is a no-nonsense, compassionate nurse and midwife in the British period drama series "Call the Midwife."
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de568b81f08190a571004261c0e8e4 |
completed | April 14, 2026, 3 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef5c11708190a7fd4c0682b6ed81 |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 9, 2026, 10:21 p.m.