Triple
T37620171
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Appaloosa-type horse |
E936045
|
entity |
| Predicate | mayHaveMarking |
P30201
|
FINISHED |
| Object | blanket pattern |
—
|
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: blanket pattern | Statement: [Appaloosa-type horse, mayHaveMarking, blanket pattern]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayHaveMarking Context triple: [Appaloosa-type horse, mayHaveMarking, blanket pattern]
-
A.
mayHaveMarkings
chosen
Indicates that an entity is permitted or able to possess certain markings or distinguishing signs.
-
B.
colorMarkings
Indicates that one entity has specific color-based markings or patterns in relation to another entity.
-
C.
distinctiveMarking
Indicates that one entity bears a unique or distinguishing visual feature or pattern that sets it apart from others.
-
D.
hasMeasurementMarkings
Indicates that one entity bears visible measurement indicators or scale markings on its surface for quantifying something.
-
E.
isMarkedAccordingTo
Indicates that one entity bears marks, labels, or annotations that conform to the rules, standards, or criteria specified by another entity or reference.
- 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_69f76ed16b748190ad6add183b1be688 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbb084760c8190a1554985d3c3cb7a |
completed | May 6, 2026, 9:20 p.m. |
| PD | Predicate disambiguation | batch_69fbadf3cb548190ba3b7514f76b790a |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.