Triple
T18933278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Courtney Gains |
E463170
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Courtney |
—
|
NE NERFINISHED |
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 Gains, givenName, Courtney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Courtney Context triple: [Courtney Gains, givenName, Courtney]
-
A.
Courtney
chosen
Courtney is a surname of Irish origin that is also commonly used as a given name.
-
B.
Courtney
"Courtney" is a song by the American nerd rock band Nerf Herder, known for their humorous, pop-punk style.
-
C.
Courtney Shayne
Courtney Shayne is the ruthless, popularity-obsessed queen bee and primary antagonist of the dark teen comedy film "Jawbreaker."
-
D.
Courtney Rawlinson
Courtney Rawlinson is a character in Bret Easton Ellis's novel "American Psycho," depicted as a socialite entangled in the shallow, drug-fueled Manhattan elite surrounding Patrick Bateman.
-
E.
Courtney Bruce
Courtney Bruce is an Australian professional netballer best known as a dominant goal keeper for the national team and in elite domestic competitions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dcfec90481909e926be9767e5779 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d3e498308190bd1594cca841199c |
completed | April 20, 2026, 7:21 a.m. |
Created at: April 10, 2026, 11:59 a.m.