Triple
T29246593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muscardinus avellanarius |
E741454
|
entity |
| Predicate | usesTorpor |
P145581
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Muscardinus avellanarius, usesTorpor, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesTorpor Context triple: [Muscardinus avellanarius, usesTorpor, yes]
-
A.
canEnterTorpor
chosen
Indicates that an entity is capable of entering a state of torpor, a reversible period of significantly reduced metabolic activity and physiological function.
-
B.
putToSleepBy
Indicates that one entity causes another entity to fall asleep or be rendered unconscious.
-
C.
hibernatesDuring
Indicates that an entity enters a state of hibernation throughout a specified time period or season.
-
D.
restingBehavior
Indicates a relationship where an entity is in a state of rest or inactivity, typically pausing movement or action for recovery or idling.
-
E.
usesPowerFor
Indicates that one entity applies or exploits a particular power, energy, or capability for a specific purpose or activity.
- 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_69f0911eba2c8190b07cd2fdf91422c9 |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f969b4cc8190afb473a2d8b110bc |
completed | May 3, 2026, 7:29 a.m. |
Created at: April 28, 2026, 12:33 p.m.