Triple
T26347640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corel WordPerfect Office |
E662818
|
entity |
| Predicate | hasPresentationProgram |
P62047
|
FINISHED |
| Object | Presentations |
—
|
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: Presentations | Statement: [Corel WordPerfect Office, hasPresentationProgram, Presentations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPresentationProgram Context triple: [Corel WordPerfect Office, hasPresentationProgram, Presentations]
-
A.
hasPublicProgram
Indicates that an entity offers or participates in a program or initiative that is accessible to the general public.
-
B.
hasPresentation
chosen
Indicates that an entity delivers, contains, or is associated with a specific presentation (such as a talk, slide deck, or formal display of information).
-
C.
hasProgramme
Indicates that an entity is associated with or offers a particular programme (such as a course of study, plan, or structured set of activities).
-
D.
hasExhibitionProgram
Indicates that an entity (such as a venue or institution) organizes or offers a structured program of exhibitions.
-
E.
hasLoungeProgram
Indicates that an entity operates, offers, or is associated with a specific lounge access program.
- 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_69ee8130fc44819094e5ab1da201cd7b |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69fcc7338120819081cb46547d60f2cb |
completed | May 7, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69fcc58566a0819082d5ea36e03bf0c6 |
completed | May 7, 2026, 5:01 p.m. |
Created at: April 26, 2026, 10:43 p.m.