Triple
T9390608
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dangerous |
E226016
|
entity |
| Predicate | includesSong |
P7178
|
FINISHED |
| Object | Give In to Me |
E682594
|
NE 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: Give In to Me | Statement: [Dangerous, includesSong, Give In to Me]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Give In to Me Context triple: [Dangerous, includesSong, Give In to Me]
-
A.
Give In to Me
chosen
"Give In to Me" is a rock-influenced power ballad by Michael Jackson featuring guitarist Slash, released as one of the singles from his 1991 album Dangerous.
-
B.
Give It To Me
"Give It To Me" is a popular Afrobeat song by Nigerian artist D'Prince, known for its catchy rhythm and club-friendly vibe.
-
C.
Give It to Me
"Give It to Me" is a 2007 electro-pop/hip hop single by Timbaland featuring Nelly Furtado and Justin Timberlake, known for its club-ready beat and perceived lyrical jabs at other artists.
-
D.
Bare Necessities
Bare Necessities is an online retailer specializing in lingerie, swimwear, and intimate apparel from a wide range of brands.
-
E.
Lean on Me
"Lean on Me" is a 1989 American drama film starring Morgan Freeman as a tough, unconventional high school principal working to reform a troubled inner-city school.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca842f7e3481908bf5bcf52e032dbd |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd510d7a9c8190a74ccdb5478dedc9 |
completed | April 1, 2026, 5:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1079272c88190b9c44f25e834f9ef |
completed | April 4, 2026, 12:44 p.m. |
Created at: March 30, 2026, 7:45 p.m.