Triple
T20698580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minion Land expansion at Universal Studios Florida |
E508716
|
entity |
| Predicate | featuresRetail |
P54721
|
FINISHED |
| Object | Evil Stuff |
—
|
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: Evil Stuff | Statement: [Minion Land expansion at Universal Studios Florida, featuresRetail, Evil Stuff]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresRetail Context triple: [Minion Land expansion at Universal Studios Florida, featuresRetail, Evil Stuff]
-
A.
featuresShop
Indicates that an entity prominently presents or includes a particular shop as one of its notable elements or offerings.
-
B.
hasRetailCharacteristic
Indicates that an entity possesses a specific attribute, feature, or quality relevant to retail contexts (such as pricing, packaging, or point-of-sale properties).
-
C.
retailConcept
Indicates that one entity represents a retail-related concept, model, or framework that characterizes or defines the nature of another entity’s retail activity or context.
-
D.
hasRetailProduct
Indicates that an entity offers, sells, or makes available a particular product in a retail context.
-
E.
featuresItem
chosen
Indicates that one entity includes, presents, or highlights another entity as a notable item or component.
- 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_69e0b4c2b2a481909e31e9cb8f81ab55 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c113e4cc8190aabc11e3f2530e32 |
completed | April 21, 2026, 12:13 a.m. |
| PD | Predicate disambiguation | batch_69e5c044d1108190b2b5d25de23f6401 |
completed | April 20, 2026, 5:57 a.m. |
Created at: April 16, 2026, 12:11 p.m.