Triple
T27775945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Honeymoon Tour |
E699184
|
entity |
| Predicate | hasMeetAndGreetOpportunities |
P30896
|
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: [The Honeymoon Tour, hasMeetAndGreetOpportunities, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeetAndGreetOpportunities Context triple: [The Honeymoon Tour, hasMeetAndGreetOpportunities, yes]
-
A.
hasIndoorMeetAndGreet
Indicates that an entity offers an indoor location where visitors can meet and interact with a specified character or representative.
-
B.
featuresCharacterMeetAndGreets
chosen
Indicates that the subject offers opportunities for visitors to meet and interact with characters in organized meet-and-greet sessions.
-
C.
hasAttractionAccess
Indicates that an entity has permission or the ability to enter, use, or benefit from a specified attraction.
-
D.
hasHospitalityComponent
Indicates that something includes, involves, or is associated with a hospitality-related element, service, or function.
-
E.
hasTimeOfSpecialAttraction
Indicates a relationship where something is associated with a specific time period during which it has a heightened or special level of attraction.
- 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_69ef6a4b5a9081909c9111396c2be3d2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f7b5ccbda481908fe1945c35e36ce8 |
completed | May 3, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
Created at: April 27, 2026, 5:06 p.m.