Triple
T12545446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ron Curry |
E299953
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Ron |
E793821
|
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: Ron | Statement: [Ron Curry, hasGivenName, Ron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ron Context triple: [Ron Curry, hasGivenName, Ron]
-
A.
Ron
Ron is a central character in the Harry Potter series, known as Harry Potter’s loyal best friend and a member of the Weasley family.
-
B.
Ron
Ron is a malfunctioning but endearing robot companion who forms an unlikely friendship with a socially awkward boy in the animated film "Ron's Gone Wrong."
-
C.
Ron
Ron is a West Chadic language spoken in parts of central Nigeria.
-
D.
Ron
Ron is a fictional assistant district attorney character, best known from the television series "Law & Order: Criminal Intent."
-
E.
Ron
chosen
Ron is the given name of American novelist Ron Currie Jr., known for his darkly comic and speculative fiction.
- 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9547f9a1c81908f54c58a116a8446 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f655801cac8190b1f9a72f8fed0399 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 9:57 p.m.