Triple
T29120304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter Bogert |
E737160
|
entity |
| Predicate | roleAtUSRobots |
P170156
|
FINISHED |
| Object | research executive |
—
|
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: research executive | Statement: [Peter Bogert, roleAtUSRobots, research executive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleAtUSRobots Context triple: [Peter Bogert, roleAtUSRobots, research executive]
-
A.
hasRobotCharacterRole
Indicates that an entity participates in a role or function specifically as a robot character within a given context or work.
-
B.
roleInTransformers
Indicates that an entity has a specific role or function within the Transformers franchise or universe.
-
C.
hasRobot
Indicates that one entity possesses, controls, or is associated with a robot.
-
D.
roleInGemini10
Indicates that an entity holds a specific role or position in the context of the Gemini 10 mission or project.
-
E.
roleForUS
Indicates that an entity serves or is designated to serve in a particular role or capacity within the context of "US" (such as a specific organization, group, or system).
- 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_69f077ed54e08190bb02a744e8121a66 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f68b121eac81909e90416207bc1157 |
completed | May 2, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f68a160374819084d720985f800dfc |
completed | May 2, 2026, 11:34 p.m. |
Created at: April 28, 2026, 11:25 a.m.