Triple
T8470738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple LaserWriter |
E200273
|
entity |
| Predicate | roleInComputing |
P24646
|
FINISHED |
| Object | helped popularize desktop publishing |
—
|
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: helped popularize desktop publishing | Statement: [Apple LaserWriter, roleInComputing, helped popularize desktop publishing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInComputing Context triple: [Apple LaserWriter, roleInComputing, helped popularize desktop publishing]
-
A.
technologyRole
chosen
Indicates the functional role or purpose that a technology plays within a system, process, or context.
-
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.
roleInText
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
-
D.
platformRole
Indicates the specific function, position, or level of responsibility an entity holds within a given platform or system.
-
E.
roleInIndustry
Indicates the specific function, position, or capacity an entity holds within a particular industry or sector.
- 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_69ca831a4f348190bfdd09250e86ae35 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4f234c481909534de6fd702f4cf |
completed | March 31, 2026, 3:14 p.m. |
| PD | Predicate disambiguation | batch_69cbd10072cc819084be1ed9ac7ebe9d |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:11 p.m.