Triple
T13125830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karcsi |
E311839
|
entity |
| Predicate | hasNickNameRole |
P36689
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Karcsi, hasNickNameRole, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNickNameRole Context triple: [Karcsi, hasNickNameRole, true]
-
A.
nicknameForRole
chosen
Indicates that one entity is an informal or alternative name commonly used to refer to a particular role or position represented by another entity.
-
B.
hasNicknameStatus
Indicates that an entity holds a particular status or classification specifically related to its nickname.
-
C.
isNickname
Indicates that one name is an informal or alternative name commonly used to refer to the same person or entity as another name.
-
D.
hasNicknamedEntityType
Indicates that an entity is associated with another entity type specifically in the role of being its nickname or informal name.
-
E.
usesNicknameOf
Indicates that one entity refers to another entity by a nickname derived from or associated with that other entity’s name.
- 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_69d806a9fe888190b081e2d9ea665d6c |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9819946808190b41335fb1054accd |
completed | April 10, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69d98043a74c81908648e6cd0b4c7f71 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:07 p.m.