Triple
T38248154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johnny (French Version) |
E1013954
|
entity |
| Predicate | characterNameInFrenchVersion |
P36851
|
FINISHED |
| Object | Johnny |
—
|
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: Johnny | Statement: [Johnny (French Version), characterNameInFrenchVersion, Johnny]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterNameInFrenchVersion Context triple: [Johnny (French Version), characterNameInFrenchVersion, Johnny]
-
A.
nameInFrench
Indicates that an entity is known or referred to by a specific name expressed in the French language.
-
B.
characterName
chosen
Indicates that an entity has a specific name used to identify its character.
-
C.
characterFullName
Indicates that the predicate specifies the complete, formal name of a character.
-
D.
languageVariantNameInFrench
Indicates the French-language name used to refer to a particular language variant.
-
E.
hasCharacterNamedAfter
Indicates that one entity has a character whose name is derived from or intentionally based on another entity.
- F. None of above.
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_69f76dd7e89c8190b7866bc85aea521b |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a00144238708190acbec3f791cc873e |
completed | May 10, 2026, 5:14 a.m. |
| PD | Predicate disambiguation | batch_6a00120244a4819090ef39070aba9d99 |
completed | May 10, 2026, 5:05 a.m. |
Created at: May 3, 2026, 4:30 p.m.