Triple
T16854574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amazon Ads |
E409750
|
entity |
| Predicate | supportsIntegration |
P203
|
FINISHED |
| Object |
Freevee
Freevee is Amazon's free, ad-supported streaming service offering a selection of movies, TV shows, and original content.
|
E358599
|
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: Freevee | Statement: [Amazon Ads, supportsIntegration, Freevee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freevee Context triple: [Amazon Ads, supportsIntegration, Freevee]
-
A.
Viki
Viki is the commonly used nickname for Viki Weisskopf, likely referring to her in informal or personal contexts.
-
B.
Zeebo
Zeebo was a Brazil-focused, low-cost 3G-enabled video game console designed to bring digital gaming to emerging markets.
-
C.
The Freebie
The Freebie is a 2010 American independent romantic drama film about a married couple who experiment with giving each other one night of sexual freedom, written and directed by Katie Aselton.
-
D.
Viddy
Viddy was a mobile social video-sharing app that allowed users to create, edit, and share short video clips with an online community.
-
E.
Xumo
Xumo is a free, ad-supported streaming television service offering a variety of live and on-demand channels and content.
- 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: Freevee Triple: [Amazon Ads, supportsIntegration, Freevee]
Generated description
Freevee is Amazon's free, ad-supported streaming service offering a selection of movies, TV shows, and original content.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Freevee Target entity description: Freevee is Amazon's free, ad-supported streaming service offering a selection of movies, TV shows, and original content.
-
A.
Viki
Viki is the commonly used nickname for Viki Weisskopf, likely referring to her in informal or personal contexts.
-
B.
Zeebo
Zeebo was a Brazil-focused, low-cost 3G-enabled video game console designed to bring digital gaming to emerging markets.
-
C.
The Freebie
The Freebie is a 2010 American independent romantic drama film about a married couple who experiment with giving each other one night of sexual freedom, written and directed by Katie Aselton.
-
D.
Viddy
Viddy was a mobile social video-sharing app that allowed users to create, edit, and share short video clips with an online community.
-
E.
Xumo
chosen
Xumo is a free, ad-supported streaming television service offering a variety of live and on-demand channels and content.
- F. None of above.
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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b37c6e808190975b14b228253029 |
completed | April 18, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00bb216fac81909d401c6b9911d1e0 |
completed | May 10, 2026, 5:06 p.m. |
| NEDg | Description generation | batch_6a00bb9b2b1881908f9f5c3dd1a2d500 |
completed | May 10, 2026, 5:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00bc3a4b888190bd190b9330e2777d |
completed | May 10, 2026, 5:11 p.m. |
Created at: April 10, 2026, 5:24 a.m.