Triple
T1851116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | D23 Expo 2017 |
E41394
|
entity |
| Predicate | hasAttendeeType |
P1284
|
FINISHED |
| Object | Disney fans |
—
|
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: Disney fans | Statement: [D23 Expo 2017, hasAttendeeType, Disney fans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAttendeeType Context triple: [D23 Expo 2017, hasAttendeeType, Disney fans]
-
A.
hasVisitorType
chosen
Indicates the type or category of visitor associated with an entity (e.g., guest, customer, tourist, patient).
-
B.
hasMemberType
Indicates that an entity includes or is associated with members belonging to a specified type or category.
-
C.
hasActivityType
Indicates the specific kind or category of activity associated with an entity or event.
-
D.
hasCampType
Indicates that an entity is associated with or classified by a particular type or category of camp.
-
E.
participantType
Indicates the specific role or category that a participant has within a given event, activity, or relationship.
- 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_69a88648cd44819093303206d96d76ad |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb32d35508190bf1c487dffbecaf0 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafdca6d8819083c66f3a29fd9fd1 |
completed | March 7, 2026, 4:55 a.m. |
Created at: March 4, 2026, 7:33 p.m.