Triple
T18133325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judy |
E434069
|
entity |
| Predicate | genderConventionInCodeNames |
P130575
|
FINISHED |
| Object | female given name for bomber-type 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: female given name for bomber-type aircraft | Statement: [Judy, genderConventionInCodeNames, female given name for bomber-type aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genderConventionInCodeNames Context triple: [Judy, genderConventionInCodeNames, female given name for bomber-type aircraft]
-
A.
namedForGender
Indicates that one entity is named in a way that reflects or is derived from a particular gender or gender-related characteristic of another entity.
-
B.
usesCodeName
Indicates that one entity refers to another entity by a code name or alias instead of its real or full designation.
-
C.
memberCodenamesBasedOn
Indicates that member codenames are determined or assigned according to a specified basis, rule, or source.
-
D.
honorificGender
Indicates that a particular honorific or title is associated with a specific gender or gendered form.
-
E.
genderCategories
Indicates the classification of an entity into one or more gender-related categories or identities.
- F. None of above. chosen
Provenance (4 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_69d8b909e8cc81908df4cc2b8ea6d11f |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4de04321c81909c0b9d47757720fd |
completed | April 19, 2026, 1:52 p.m. |
| PD | Predicate disambiguation | batch_69e43317d11c81908d1dc14921566b47 |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f5ae2c8190b11dee46534fa5a9 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:29 a.m.