Triple
T3235515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney Vacation Club villas |
E67844
|
entity |
| Predicate | typicalGuestProfile |
P41733
|
FINISHED |
| Object | repeat Walt Disney World visitors |
—
|
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: repeat Walt Disney World visitors | Statement: [Disney Vacation Club villas, typicalGuestProfile, repeat Walt Disney World visitors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalGuestProfile Context triple: [Disney Vacation Club villas, typicalGuestProfile, repeat Walt Disney World visitors]
-
A.
typicalGuests
Indicates the usual or most common guests associated with a particular host, place, or event.
-
B.
typicalProfile
chosen
Indicates that an entity represents the standard or most representative profile or pattern for another entity.
-
C.
typicalPlayerProfile
Indicates the usual or characteristic attributes, behaviors, or demographics associated with a representative player in a given context.
-
D.
typicalSpeaker
Indicates that the subject is a prototypical or characteristic speaker or source of utterances in the context of the object.
-
E.
typicalRole
Indicates that one entity serves as the usual, characteristic, or commonly expected role or function of another entity.
- 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_69ad858d27348190abb61c280b4c86a9 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaede0bdc8190a466f11bf2c50836 |
completed | March 8, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69ada4159e0481908cbbdd750f5e08c7 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:08 p.m.