Triple
T9399961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimberella |
E226441
|
entity |
| Predicate | feedingTraceType |
P88735
|
FINISHED |
| Object | scratch marks on microbial mats |
—
|
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: scratch marks on microbial mats | Statement: [Kimberella, feedingTraceType, scratch marks on microbial mats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: feedingTraceType Context triple: [Kimberella, feedingTraceType, scratch marks on microbial mats]
-
A.
feedingType
Indicates the manner or method by which one entity provides nourishment or food to another.
-
B.
feedingStructure
Indicates a relationship where one entity serves as the anatomical or mechanical structure used by another entity to obtain or ingest food.
-
C.
trackingType
Indicates the method or category by which an entity’s movement, status, or progress is monitored or recorded.
-
D.
feedingSpecialization
Indicates a relationship where an entity is specialized or adapted to feed on a particular type or range of food resources.
-
E.
includesFeedingType
Indicates that one entity encompasses or specifies a particular type or category of feeding associated with 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_69ca843170f88190800a8ab2b5fc568e |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd5156b9588190bafb6b1c3ee3c0ed |
completed | April 1, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69cca545b2448190a4297312e39c21ac |
completed | April 1, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69cca89b3368819087a3d69270c1f185 |
completed | April 1, 2026, 5:09 a.m. |
Created at: March 30, 2026, 7:46 p.m.