Triple
T25460016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nelly |
E638018
|
entity |
| Predicate | name type |
P1081
|
FINISHED |
| Object | hypocorism |
—
|
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: hypocorism | Statement: [Nelly, name type, hypocorism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: name type Context triple: [Nelly, name type, hypocorism]
-
A.
nameType
chosen
Indicates the specific category or type of a name associated with an entity (e.g., legal name, nickname, alias, or preferred name).
-
B.
namesakeType
Indicates the specific kind or category of namesake relationship that exists between two entities (for example, one being named after the other as a person, place, event, or object).
-
C.
nameOf
Indicates that one entity is the name or designation of another entity.
-
D.
nameBearerType
Indicates the specific role or capacity in which an entity bears or carries a given name (e.g., as a person, place, organization, or other type of name bearer).
-
E.
nameElement
Indicates that one entity serves as the name or label assigned to another entity or element.
- 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_69e75db8bab08190baca80b4a8c315fd |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f72a452c8190b53c90a8a725dd69 |
completed | May 2, 2026, 1:07 p.m. |
| PD | Predicate disambiguation | batch_69f4683b34748190818428489a226124 |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 21, 2026, 2:11 p.m.