Triple
T9004129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WWDC 2019 |
E215100
|
entity |
| Predicate | hasNumberOfSessions |
P6891
|
FINISHED |
| Object | over 100 technical sessions |
—
|
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: over 100 technical sessions | Statement: [WWDC 2019, hasNumberOfSessions, over 100 technical sessions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfSessions Context triple: [WWDC 2019, hasNumberOfSessions, over 100 technical sessions]
-
A.
hasOnlineSessions
Indicates that an entity conducts or offers sessions, meetings, or activities via the internet rather than solely in person.
-
B.
sessionCount
chosen
Indicates the number of distinct sessions associated with an entity or interaction context.
-
C.
hasSession
Indicates that an entity is associated with, participates in, or contains a particular session instance.
-
D.
minimumSessionsPerYear
Indicates the smallest number of sessions that must occur within a one-year period.
-
E.
heldSessionsIn
Indicates that an entity organized or conducted one or more sessions, meetings, or events at a specified location or venue.
- 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_69ca83a12d648190b1e4fe11e8a31890 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6959497c8190a748c78504dd2eb6 |
completed | April 1, 2026, 12:39 a.m. |
| PD | Predicate disambiguation | batch_69cc5edd6cb48190b4fc6d6ca0418056 |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:05 p.m.