Triple
T34286826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sawyer |
E879761
|
entity |
| Predicate | hasEndEffectorInterface |
P193211
|
FINISHED |
| Object | electric gripper interface |
—
|
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: electric gripper interface | Statement: [Sawyer, hasEndEffectorInterface, electric gripper interface]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEndEffectorInterface Context triple: [Sawyer, hasEndEffectorInterface, electric gripper interface]
-
A.
endEffectorType
Indicates the specific kind or category of end effector associated with or used by an entity.
-
B.
numberOfEndEffectors
Indicates the quantity of end effectors associated with or attached to a given system, mechanism, or entity.
-
C.
hasActuatorType
Indicates that an entity is equipped with or uses a specific type or category of actuator.
-
D.
hasCommunicationInterface
Indicates that one entity provides or supports a specific means or channel through which it can communicate or exchange data with another entity or system.
-
E.
isFullyRobotic
Indicates that the entity operates entirely through robotic mechanisms without human biological components or manual control.
- 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_69f349b6df1c81908e5e5b6c2ab6409b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
| PDg | Predicate description generation | batch_69fd3a6905b88190ae12b43576f4cc63 |
completed | May 8, 2026, 1:20 a.m. |
Created at: May 1, 2026, 1:57 a.m.