Triple
T32403024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Johnnie |
E828001
|
entity |
| Predicate | hasMasculineUsagePatternSimilarTo |
P15475
|
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: [Johnnie, hasMasculineUsagePatternSimilarTo, Johnny]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMasculineUsagePatternSimilarTo Context triple: [Johnnie, hasMasculineUsagePatternSimilarTo, Johnny]
-
A.
hasMasculineForm
chosen
Indicates that an entity has a corresponding masculine grammatical or lexical form.
-
B.
hasAlternativeGenderUsage
Indicates that an entity is used with a different or non-standard gender form in certain contexts or usages.
-
C.
hasFemaleFormOf
Indicates that one entity is the specifically female version or form of another, more general or differently gendered entity.
-
D.
hasFeminineFormInSomeLanguages
Indicates that the referenced entity has a distinct feminine grammatical or lexical form in at least one language.
-
E.
hasTypicalGenderAssociation
Indicates that one entity is commonly or culturally associated with a particular gender more than with other genders.
- 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_69f34919342c8190a4c3bf35a90d4e58 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a008ac37dc081908d360574912f40ec |
completed | May 10, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_6a008a67d73881909855ab4cfca3c399 |
completed | May 10, 2026, 1:38 p.m. |
Created at: May 1, 2026, 12:53 a.m.