Triple
T2705171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | blue duck |
E59324
|
entity |
| Predicate | sexDimorphism |
P1333
|
FINISHED |
| Object | male has more pronounced whistling call |
—
|
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 has more pronounced whistling call | Statement: [blue duck, sexDimorphism, male has more pronounced whistling call]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sexDimorphism Context triple: [blue duck, sexDimorphism, male has more pronounced whistling call]
-
A.
sexualDimorphism
chosen
Indicates differences in physical characteristics between males and females of a species that are systematically associated with their sex.
-
B.
sexes
Indicates that one entity engages in sexual activity with another entity.
-
C.
sexOrGender
Indicates that one entity has a specified biological sex or socially constructed gender identity.
-
D.
sexDeterminationDetail
Indicates the specific mechanism or factors by which an organism’s sex is determined.
-
E.
hasGenderDistinction
Indicates that a relationship, classification, or linguistic form differentiates entities based on gender categories.
- 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_69ab4ac66bc88190b9e4afa5fc843f72 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda559a908190ad5d92c11a398a03 |
completed | March 7, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69abd82062988190b4292f242ad70b2c |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:55 p.m.