Triple
T29757484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rex |
E753068
|
entity |
| Predicate | genderCodeConvention |
P130575
|
FINISHED |
| Object | male name for fighter aircraft |
—
|
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: male name for fighter aircraft | Statement: [Rex, genderCodeConvention, male name for fighter aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderCodeConvention Context triple: [Rex, genderCodeConvention, male name for fighter aircraft]
-
A.
genderRule
Indicates a rule or constraint that determines how gender-related properties or classifications should be assigned or interpreted in a given context.
-
B.
genderConventionInCodeNames
chosen
Indicates that a particular gender-based convention is used when assigning or interpreting code names.
-
C.
genderConfiguration
Indicates how the genders of the involved entities are arranged or combined within a particular relationship or context.
-
D.
genderCategories
Indicates the classification of an entity into one or more gender-related categories or identities.
-
E.
genderAtBeginning
Indicates that an entity had a specified gender at the start of a defined time period or event.
- 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_69f0d62c84cc8190846f80ae04fdf8ec |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f68a16debc8190a12f5f65ced055d7 |
completed | May 2, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 28, 2026, 7:57 p.m.