Triple
T33642700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Founding of the State of Liberty Spiritual |
E861873
|
entity |
| Predicate | hasGenderOfCreator |
P25113
|
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: [The Founding of the State of Liberty Spiritual, hasGenderOfCreator, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderOfCreator Context triple: [The Founding of the State of Liberty Spiritual, hasGenderOfCreator, female]
-
A.
creatorSexOrGender
chosen
Indicates that the specified sex or gender is the sex or gender of the creator of the referenced work or entity.
-
B.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
-
C.
hasAuthorGender
Indicates that an entity (such as a work or publication) is associated with an author of a specified gender.
-
D.
hasGenderLine
Indicates that there is a specified gender-related boundary, division, or categorization between the associated entities.
-
E.
hadGender
Indicates that an entity possessed a specific gender.
- 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_69f3498280c48190bcc3494017d14234 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fd485f57dc8190820365396d041991 |
completed | May 8, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69fd47d35da081908bec8901018d186c |
completed | May 8, 2026, 2:17 a.m. |
Created at: May 1, 2026, 1:42 a.m.