Triple
T21839599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mecistops |
E539218
|
entity |
| Predicate | adaptationForFeeding |
P84287
|
FINISHED |
| Object | catching fish |
—
|
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: catching fish | Statement: [Mecistops, adaptationForFeeding, catching fish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adaptationForFeeding Context triple: [Mecistops, adaptationForFeeding, catching fish]
-
A.
feedingHabitat
Indicates the type of environment or location where an organism typically obtains and consumes its food.
-
B.
notableFeedingBehavior
chosen
Indicates a characteristic way or pattern in which an entity typically obtains or consumes food that is considered distinctive or noteworthy.
-
C.
feedingSpecialization
Indicates a relationship where an entity is specialized or adapted to feed on a particular type or range of food resources.
-
D.
feedingStructure
Indicates a relationship where one entity serves as the anatomical or mechanical structure used by another entity to obtain or ingest food.
-
E.
feedingType
Indicates the manner or method by which one entity provides nourishment or food to another.
- 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_69e0c475cda88190987d08f23caebdc1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0a7aaa4f081909e869d2e81b07b91 |
completed | April 28, 2026, 12:27 p.m. |
| PD | Predicate disambiguation | batch_69e6be8c14748190bdcc44a14d50bea4 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:55 p.m.