Triple
T2836615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple Worldwide Developers Conference 2006 |
E62366
|
entity |
| Predicate | hasWorkshops |
P42933
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Apple Worldwide Developers Conference 2006, hasWorkshops, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorkshops Context triple: [Apple Worldwide Developers Conference 2006, hasWorkshops, yes]
-
A.
hasTeachingActivity
Indicates that an entity engages in or is associated with a specific teaching-related activity or instructional role.
-
B.
hasTeaching
Indicates that one entity provides instruction or educational guidance to another entity.
-
C.
hasNumberOfLessons
Indicates the specific count of lessons associated with an entity.
-
D.
hasEducationalProgram
Indicates that an entity offers, runs, or is associated with a specific educational program.
-
E.
conferenceCoachedIn
Indicates that a person provided coaching or guidance during a specific conference.
- 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_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdeec60a08190b76b52042713d647 |
completed | March 7, 2026, 8:16 a.m. |
| PD | Predicate disambiguation | batch_69abdd0ce8b08190ba28c192988f38ce |
completed | March 7, 2026, 8:08 a.m. |
| PDg | Predicate description generation | batch_69abde4895dc819097c396c5d31ac1d1 |
completed | March 7, 2026, 8:14 a.m. |
Created at: March 6, 2026, 10:01 p.m.