Triple
T230447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Cailliau |
E4398
|
entity |
| Predicate | roleAtCERN |
P7507
|
FINISHED |
| Object | computer systems engineer |
—
|
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: computer systems engineer | Statement: [Robert Cailliau, roleAtCERN, computer systems engineer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleAtCERN Context triple: [Robert Cailliau, roleAtCERN, computer systems engineer]
-
A.
roleInvolves
Indicates that a particular role includes or requires participation in a specified activity, responsibility, or function.
-
B.
roleInEcosystem
Indicates the specific function or contribution an entity has within an ecosystem and how it interacts with other components of that system.
-
C.
identificationRole
Indicates that an entity serves as an identifier or plays a role in uniquely distinguishing or recognizing another entity.
-
D.
hasInternationalOrganizationRole
chosen
Indicates that an entity holds or has held a specific role, position, or function within an international organization.
-
E.
positionInWork
Indicates the specific role, rank, or placement an entity holds within a larger work or structured composition.
- 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_69a257363ffc81909757bde7ab3404da |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25e0868708190ad551ca06cc57f4a |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b5a075081909b0e9b88c1492d5a |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.