Triple
T21178706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steve Capper |
E521883
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Steve |
—
|
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: Steve | Statement: [Steve Capper, givenName, Steve]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Context triple: [Steve Capper, givenName, Steve]
-
A.
Steve
chosen
Steve is a masculine given name commonly used in English-speaking countries, often as a short form of Stephen or Steven.
-
B.
Steve
Steve is the central protagonist of the adventure story "High Seas," around whom the main events and conflicts of the narrative revolve.
-
C.
Steve
Steve is the given name of Steve Bartek, an American guitarist, composer, and longtime collaborator with the band Oingo Boingo and film composer Danny Elfman.
-
D.
Steve
Steve is a central character in the animated film "Wonder Park," depicted as one of the imaginative figures who inhabit the fantastical amusement park created by the protagonist.
-
E.
Steve
Steve is the central protagonist of the story in Alexandra's Project, around whom the film’s psychological drama and tension revolve.
- 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_69e0b50ef1d48190b063aa342667df22 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7301b41908190bc104aa748a0346d |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 3 p.m.