Triple
T18037141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freddy Eastwood |
E431537
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Freddy |
—
|
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: Freddy | Statement: [Freddy Eastwood, givenName, Freddy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freddy Context triple: [Freddy Eastwood, givenName, Freddy]
-
A.
Freddy
chosen
Freddy is a common diminutive or nickname for the given name Alfred.
-
B.
Freddy
Freddy is a central character in Steve Martin’s absurdist stage play "Picasso at the Lapin Agile," typically portrayed as the bartender who observes and comments on the surreal meeting of Picasso and Einstein.
-
C.
Freddy
Freddy is a fictional character played by British-Egyptian actor Khalid Abdalla.
-
D.
Freddy Gale
Freddy Gale is the tormented, vengeance-obsessed protagonist of the film "The Crossing Guard," portrayed by Jack Nicholson as a grieving father consumed by his desire to confront the drunk driver who killed his daughter.
-
E.
Freddy Krueger
Freddy Krueger is a fictional supernatural serial killer known for haunting and murdering teenagers in their dreams, recognizable by his burned face, bladed glove, and striped sweater.
- 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4be3a80508190b667c3f6d14f5c84 |
completed | April 19, 2026, 11:36 a.m. |
Created at: April 10, 2026, 10:25 a.m.