Triple
T26633223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giovannino |
E668559
|
entity |
| Predicate | hasEquivalentDiminutiveInOtherLanguage |
P76128
|
FINISHED |
| Object | Little John |
—
|
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: Little John | Statement: [Giovannino, hasEquivalentDiminutiveInOtherLanguage, Little John]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEquivalentDiminutiveInOtherLanguage Context triple: [Giovannino, hasEquivalentDiminutiveInOtherLanguage, Little John]
-
A.
hasDiminutive
Indicates that one entity is a diminutive form or smaller/affectionate variant of another entity.
-
B.
equivalentEpithetLanguage
chosen
Indicates that two epithets are expressed in different languages but convey the same meaning or designation.
-
C.
hasLanguageFormOf
Indicates that one entity is a specific linguistic form, expression, or realization of the language used by another entity.
-
D.
hasAlternativeNameOfParentLanguage
Indicates that an entity has an alternative or variant name derived from or associated with the name of its parent language.
-
E.
hasDialectalCounterpart
Indicates that one linguistic form has a corresponding equivalent or variant in another dialect.
- 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_69ee9d0024b8819090a7c8cf669a3b6c |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f61a17a7788190946f7e32d63cd43f |
completed | May 2, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69f611ab768c8190b1849c15a3e59dda |
completed | May 2, 2026, 3 p.m. |
Created at: April 27, 2026, 2:26 a.m.