Triple
T247089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indian peafowl |
E5060
|
entity |
| Predicate | trainFeatures |
P5084
|
FINISHED |
| Object | eye-like spots called ocelli |
—
|
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: eye-like spots called ocelli | Statement: [Indian peafowl, trainFeatures, eye-like spots called ocelli]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trainFeatures Context triple: [Indian peafowl, trainFeatures, eye-like spots called ocelli]
-
A.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
-
B.
training
Indicates that one entity is teaching, coaching, or otherwise helping another entity acquire or improve a skill, behavior, or capability.
-
C.
typicalFeatures
chosen
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
D.
notableTrain
Indicates that there is a train or rail service associated with the subject that is considered notable or significant in some way.
-
E.
keyFeature
Indicates that something is a primary, distinguishing, or most important feature of an 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d13b8088190a3f48f0388d57496 |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b63b0bc8190864d7324d339fb48 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.