Triple
T5047170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Courtney Hodges |
E113694
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Courtney |
E89699
|
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 | Statement: [Courtney Hodges, givenName, Courtney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Courtney Context triple: [Courtney Hodges, givenName, Courtney]
-
A.
Courtney
chosen
Courtney is a surname of Irish origin that is also commonly used as a given name.
-
B.
Courtney Lee
Courtney Lee is an American former professional basketball shooting guard who played in the NBA for multiple teams, including the Orlando Magic, Boston Celtics, and Dallas Mavericks.
-
C.
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.
-
D.
Courtney Gains
Courtney Gains is an American character actor known for his offbeat and often unsettling roles in films such as "Children of the Corn," "Can't Buy Me Love," and numerous 1980s cult classics.
-
E.
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."
- 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_69bd44391fc48190a311ce9c826c209b |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd740002b48190bc7aa176d734c589 |
completed | March 20, 2026, 4:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be9c9143a081909132c66eb9fc91db |
completed | March 21, 2026, 1:26 p.m. |
Created at: March 20, 2026, 1:37 p.m.