Triple
T20538022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney water parks |
E504250
|
entity |
| Predicate | hasMarketingPoint |
P140461
|
FINISHED |
| Object | themed aquatic adventures |
—
|
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: themed aquatic adventures | Statement: [Disney water parks, hasMarketingPoint, themed aquatic adventures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarketingPoint Context triple: [Disney water parks, hasMarketingPoint, themed aquatic adventures]
-
A.
hasMarketingElement
Indicates that one entity includes, is associated with, or makes use of a particular marketing-related component or feature.
-
B.
hasMarketingCategory
Indicates that an entity is associated with a specific marketing category or segment used for classification or targeting.
-
C.
hasMarketingIcon
Indicates that an entity is associated with, or represented by, a specific marketing-related icon or symbol.
-
D.
hasMarketingClaim
Indicates that an entity asserts or is associated with a specific marketing claim about a product, service, or brand.
-
E.
hasMarketingTarget
Indicates that an entity is aimed at or intended to appeal to a specific marketing audience or segment.
- F. None of above. chosen
Provenance (4 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_69e0b4b476648190bc6019622ae54d3c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a29006008190aa1ee3224c75ff4b |
completed | April 20, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69e59fe5592c8190bb6122b784496d02 |
completed | April 20, 2026, 3:39 a.m. |
| PDg | Predicate description generation | batch_69e5a6a824748190bbe6192d73f3c613 |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 16, 2026, 11:37 a.m.