Triple
T18878150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alice |
E461743
|
entity |
| Predicate | hasGenderConvention |
P133302
|
FINISHED |
| Object | female |
—
|
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 | Statement: [Alice, hasGenderConvention, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderConvention Context triple: [Alice, hasGenderConvention, female]
-
A.
hasGenderInSomeTraditions
Indicates that, in at least some cultural, religious, or historical traditions, the subject is regarded as having a specific gender.
-
B.
hasGenderFormat
Indicates that something is associated with or expressed in a particular gender-related format or representation.
-
C.
hasGenderDistinction
Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
-
D.
hasGenderSystem
Indicates that an entity employs or is characterized by a particular system for categorizing gender.
-
E.
hasGenderNeutrality
Indicates that something (such as a term, form, or expression) is neutral with respect to gender and does not specify or imply any particular gender.
- 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c3cfc4408190a7ae91459f75be52 |
completed | April 20, 2026, 6:12 a.m. |
| PD | Predicate disambiguation | batch_69e48d22dde8819093b1d963bd673365 |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e4978813d081908eaf25bb727fc6cf |
completed | April 19, 2026, 8:51 a.m. |
Created at: April 10, 2026, 11:57 a.m.