Triple
T32358090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pegusa |
E826786
|
entity |
| Predicate | hasEyePosition |
P115176
|
FINISHED |
| Object | both eyes on one side of head |
—
|
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: both eyes on one side of head | Statement: [Pegusa, hasEyePosition, both eyes on one side of head]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEyePosition Context triple: [Pegusa, hasEyePosition, both eyes on one side of head]
-
A.
hasEyes
Indicates that an entity possesses eyes as physical features.
-
B.
eyeLocation
chosen
Indicates the spatial position or placement of an eye relative to a reference object or coordinate system.
-
C.
hasHeadPosition
Indicates the specific spatial position or orientation of an entity’s head relative to a reference frame or context.
-
D.
hasInclinationToLineOfSight
Indicates that one entity is oriented or directed in such a way that it tends toward having a line of sight to another entity or location.
-
E.
hasFieldOfView
Indicates that one entity possesses a visual coverage area within which it can perceive or detect other entities or regions.
- 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_69f34915a2588190bb3178f5ec2f48f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6be90f8e08190a3415ac7cb60dc25 |
completed | May 3, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69f6ba6cef208190bc5cd43d96127004 |
completed | May 3, 2026, 3:01 a.m. |
Created at: May 1, 2026, 12:49 a.m.