Triple
T17058406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2009 New York International Auto Show (first generation) |
E413888
|
entity |
| Predicate | hasAttendees |
P2434
|
FINISHED |
| Object | automakers |
—
|
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: automakers | Statement: [2009 New York International Auto Show (first generation), hasAttendees, automakers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAttendees Context triple: [2009 New York International Auto Show (first generation), hasAttendees, automakers]
-
A.
hasParticipants
chosen
Indicates that an event, activity, or situation involves one or more entities as participants in it.
-
B.
laterAttends
Indicates that one entity attends an event or place at a time later than another referenced attendance.
-
C.
mayAttend
Indicates that an entity is permitted or eligible to be present at or participate in a particular event, activity, or gathering.
-
D.
hasAttendanceType
Indicates the specific category or mode of attendance associated with an event or participant (e.g., in-person, virtual, hybrid).
-
E.
hasMeeting
Indicates that one entity is scheduled to participate in or hold a meeting with another entity or at a specific time or place.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3db7b553c81908ec70ba0d0988710 |
completed | April 18, 2026, 7:28 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:34 a.m.