Triple
T5264408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Keery |
E118903
|
entity |
| Predicate | appearsIn |
P795
|
FINISHED |
| Object |
Spree
Spree is a dark satirical horror-thriller film about a rideshare driver obsessed with social media fame, starring Joe Keery.
|
E507339
|
NE FINISHED |
How this triple was built (4 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: Spree | Statement: [Joe Keery, appearsIn, Spree]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spree Context triple: [Joe Keery, appearsIn, Spree]
-
A.
Spree
The Spree is a major river in eastern Germany that flows through the heart of Berlin and is central to the city's landscape and history.
-
B.
WooCommerce
WooCommerce is a widely used open-source eCommerce plugin for WordPress that enables users to create and manage online stores.
-
C.
Magento
Magento is an open-source e-commerce platform widely used by businesses to build and manage online stores with extensive customization and scalability.
-
D.
Shopian
Shopian is a town in the southern part of Jammu and Kashmir, India, known historically as an important trading hub and gateway along the ancient Mughal Road.
-
E.
Stripe
Stripe is a leading financial technology company that provides online payment processing and related services for internet businesses worldwide.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Spree Triple: [Joe Keery, appearsIn, Spree]
Generated description
Spree is a dark satirical horror-thriller film about a rideshare driver obsessed with social media fame, starring Joe Keery.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Spree Target entity description: Spree is a dark satirical horror-thriller film about a rideshare driver obsessed with social media fame, starring Joe Keery.
-
A.
Spree
The Spree is a major river in eastern Germany that flows through the heart of Berlin and is central to the city's landscape and history.
-
B.
WooCommerce
WooCommerce is a widely used open-source eCommerce plugin for WordPress that enables users to create and manage online stores.
-
C.
Magento
Magento is an open-source e-commerce platform widely used by businesses to build and manage online stores with extensive customization and scalability.
-
D.
Shopian
Shopian is a town in the southern part of Jammu and Kashmir, India, known historically as an important trading hub and gateway along the ancient Mughal Road.
-
E.
Stripe
Stripe is a leading financial technology company that provides online payment processing and related services for internet businesses worldwide.
- F. None of above. chosen
Provenance (5 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_69bd446a42c88190b7ecbef006561d55 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bd4a9888190a79ef8e64c764f86 |
completed | March 20, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe8b787881909be9c01d1ba52561 |
completed | March 21, 2026, 8:24 p.m. |
| NEDg | Description generation | batch_69beff76290c819099a08cd1d5397004 |
completed | March 21, 2026, 8:28 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69befffc0e388190a02624d4f466a2a9 |
completed | March 21, 2026, 8:30 p.m. |
Created at: March 20, 2026, 1:51 p.m.