Triple
T12329892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luke Perry |
E293930
|
entity |
| Predicate | appearedIn |
P795
|
FINISHED |
| Object |
What I Like About You
What I Like About You is an early-2000s American teen sitcom that follows two sisters navigating life, love, and growing up together in New York City.
|
E976069
|
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: What I Like About You | Statement: [Luke Perry, appearedIn, What I Like About You]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: What I Like About You Context triple: [Luke Perry, appearedIn, What I Like About You]
-
A.
Do Like You
"Do Like You" is a song by Stevie Wonder from his acclaimed 1980 album *Hotter than July*.
-
B.
What I Like
"What I Like" is a song featured on the soundtrack of the 1993 crime-romance film *True Romance*.
-
C.
Girls Like You
"Girls Like You" is a pop song by Maroon 5, widely known for its catchy melody and a hit remix featuring rapper Cardi B that topped charts worldwide.
-
D.
Girls Like You
"Girls Like You" is a song by American rapper Miguel from his debut studio album "All I Want Is You."
-
E.
Whatever You Like
"Whatever You Like" is a popular hip hop and R&B single by American rapper T.I., known for its catchy hook and themes of luxury and generosity in romantic relationships.
- 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: What I Like About You Triple: [Luke Perry, appearedIn, What I Like About You]
Generated description
What I Like About You is an early-2000s American teen sitcom that follows two sisters navigating life, love, and growing up together in New York City.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: What I Like About You Target entity description: What I Like About You is an early-2000s American teen sitcom that follows two sisters navigating life, love, and growing up together in New York City.
-
A.
Do Like You
"Do Like You" is a song by Stevie Wonder from his acclaimed 1980 album *Hotter than July*.
-
B.
What I Like
"What I Like" is a song featured on the soundtrack of the 1993 crime-romance film *True Romance*.
-
C.
Girls Like You
"Girls Like You" is a pop song by Maroon 5, widely known for its catchy melody and a hit remix featuring rapper Cardi B that topped charts worldwide.
-
D.
Girls Like You
"Girls Like You" is a song by American rapper Miguel from his debut studio album "All I Want Is You."
-
E.
Whatever You Like
"Whatever You Like" is a popular hip hop and R&B single by American rapper T.I., known for its catchy hook and themes of luxury and generosity in romantic relationships.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e9114f48190988b84eaec2e810f |
completed | May 2, 2026, 3:56 p.m. |
| NEDg | Description generation | batch_69f61fd2429c8190a8a7c46c312e262d |
completed | May 2, 2026, 4:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f623fbb32081909b7daa515eebf75d |
completed | May 2, 2026, 4:19 p.m. |
Created at: April 8, 2026, 9:53 p.m.