Triple
T15987468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jason Morgan |
E387733
|
entity |
| Predicate | hasSpouse |
P13
|
FINISHED |
| Object | Courtney Matthews |
E1362082
|
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: Courtney Matthews | Statement: [Jason Morgan, hasSpouse, Courtney Matthews]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Courtney Matthews Context triple: [Jason Morgan, hasSpouse, Courtney Matthews]
-
A.
Courtney Matthews
chosen
Courtney Matthews is a fictional character from the soap opera "General Hospital," known for her complex relationships and dramatic storylines in Port Charles.
-
B.
Courtney Hicks
Courtney Hicks is an American figure skater known for her powerful jumping ability and competitive performances on the national and international stage.
-
C.
Courtney Eaton
Courtney Eaton is an Australian actress and model best known for her roles in action and fantasy films such as "Mad Max: Fury Road" and "Gods of Egypt."
-
D.
Courtney Richards
Courtney Richards is the wife of renowned American sportscaster Jim Nantz and is known for her presence alongside him at public and sporting events.
-
E.
Courtney Richards
Courtney Richards is a relatively obscure individual whose publicly available information is limited, making it difficult to identify a widely recognized role or achievement associated with the name.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1575993948190a05d60fc9d0c05fa |
completed | April 16, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0700c341c08190962c16d616a6e31a |
completed | May 15, 2026, 11:17 a.m. |
Created at: April 10, 2026, 4:54 a.m.