Triple
T36408374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kelevra |
E896809
|
entity |
| Predicate | usedAsCharacterNameElement |
P198247
|
FINISHED |
| Object | Slevin Kelevra |
—
|
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: Slevin Kelevra | Statement: [Kelevra, usedAsCharacterNameElement, Slevin Kelevra]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsCharacterNameElement Context triple: [Kelevra, usedAsCharacterNameElement, Slevin Kelevra]
-
A.
usesCharactersAs
Indicates that one entity employs or incorporates specific characters (such as letters, symbols, or glyphs) from another entity for its representation or functioning.
-
B.
hasCharacterNamedAfter
Indicates that one entity has a character whose name is derived from or intentionally based on another entity.
-
C.
usesCharacter
Indicates that one entity employs, incorporates, or relies on a particular character (such as a symbol, letter, or persona) in its form, function, or representation.
-
D.
characterSetName
Indicates the name assigned to a particular character set used for encoding or representing characters.
-
E.
characterName
Indicates that an entity has a specific name used to identify its character.
- F. None of above. chosen
Provenance (4 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_69f76e53b81081908d3b81860593f38a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fed48d8e148190a99c0aea29f8a3ee |
completed | May 9, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fed3c82a24819095e614e31ac0307f |
completed | May 9, 2026, 6:27 a.m. |
| PDg | Predicate description generation | batch_69fed48c92ec8190b3be88880d86de86 |
completed | May 9, 2026, 6:30 a.m. |
Created at: May 3, 2026, 4:10 p.m.