Triple
T16234498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lightning Bolt |
E394068
|
entity |
| Predicate | refersToGenderOfPerson |
P122275
|
FINISHED |
| Object | male |
—
|
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 | Statement: [Lightning Bolt, refersToGenderOfPerson, male]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToGenderOfPerson Context triple: [Lightning Bolt, refersToGenderOfPerson, male]
-
A.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
-
B.
genderOfPersona
Indicates the gender identity associated with a given persona.
-
C.
genderImplication
Indicates that one entity’s gender suggests, constrains, or determines the possible or likely gender of another entity.
-
D.
hasGenderInterpretation
Indicates that an entity is associated with a particular interpretation or understanding of gender.
-
E.
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.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24559af48819092e4b466778b07e2 |
completed | April 17, 2026, 2:36 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
| PDg | Predicate description generation | batch_69e21e55a2388190b29a045a8c608ba4 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:04 a.m.