Triple
T2579834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White bass |
E57061
|
entity |
| Predicate | bodyMarkings |
P32310
|
FINISHED |
| Object | dark horizontal stripes on sides |
—
|
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: dark horizontal stripes on sides | Statement: [White bass, bodyMarkings, dark horizontal stripes on sides]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bodyMarkings Context triple: [White bass, bodyMarkings, dark horizontal stripes on sides]
-
A.
distinctiveMarking
chosen
Indicates that one entity bears a unique or distinguishing visual feature or pattern that sets it apart from others.
-
B.
hasTattoo
Indicates that one entity bears a tattoo on their body.
-
C.
mayHaveMarkings
Indicates that an entity is permitted or able to possess certain markings or distinguishing signs.
-
D.
legCharacteristic
Indicates a characteristic, property, or attribute that specifically pertains to the legs of an entity.
-
E.
hasPhysicalFeature
Indicates that one entity possesses or exhibits a specific physical characteristic or feature of another entity.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3a9fd3c8190a521931e40cd801c |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0cfeae08190aed03866ba071c5c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:49 p.m.