Triple
T8632719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Advanced Graphics Architecture |
E204440
|
entity |
| Predicate | roleOfLisa |
P84349
|
FINISHED |
| Object | video display controller |
—
|
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: video display controller | Statement: [Advanced Graphics Architecture, roleOfLisa, video display controller]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleOfLisa Context triple: [Advanced Graphics Architecture, roleOfLisa, video display controller]
-
A.
roleOfJennifer Morris
Indicates that Jennifer Morris holds or performs a particular role, position, or function in relation to another entity or context.
-
B.
familyOrganizerRole
Indicates the specific role or capacity an individual holds as the organizer or manager within a family group or household.
-
C.
typicalRole
Indicates that one entity serves as the usual, characteristic, or commonly expected role or function of another entity.
-
D.
roleInTSEliotLife
Indicates the specific role, involvement, or significance an entity had in T. S. Eliot’s life.
-
E.
roleInDialogue
Indicates that an entity participates in a dialogue with a specific conversational role (e.g., speaker, listener, moderator) relative to other participants.
- 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_69ca834b903c8190add96cc651e1a477 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc47944d1c819081f448f14d04bf9d |
completed | March 31, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69cc455d6d448190a2da2a319ac78c37 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc479284a8819099b0b0d879af3372 |
completed | March 31, 2026, 10:15 p.m. |
Created at: March 30, 2026, 6:27 p.m.