Triple
T17544153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Petter |
E427280
|
entity |
| Predicate | hasCognate |
P2525
|
FINISHED |
| Object | Peter |
—
|
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: Peter | Statement: [Petter, hasCognate, Peter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Context triple: [Petter, hasCognate, Peter]
-
A.
Peter
Peter is one of the two central characters in Edward Albee’s one-act play "The Zoo Story," portrayed as a reserved, middle-class man whose encounter with the volatile Jerry leads to a tense and existential confrontation.
-
B.
Peter
Peter is the sensible and responsible leader of Enid Blyton’s Secret Seven children’s detective club.
-
C.
Peter
Peter is the sensible, rule-abiding leader of Enid Blyton’s Secret Seven children’s detective club.
-
D.
Peter
Peter is one of the three allegorical brothers in Jonathan Swift’s satirical work "A Tale of a Tub," representing the excesses and corruptions of the Roman Catholic Church.
-
E.
Peter
Peter is the young, adventurous orphan who becomes the boy that never grows up in the Peter and the Starcatcher prequel to the Peter Pan story.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69d889df6dc081908f67dbadc03c07ee |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4545fe29c8190a586c75419fa14ea |
completed | April 19, 2026, 4:04 a.m. |
Created at: April 10, 2026, 5:49 a.m.