Triple
T13672324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ali Kiba |
E327780
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Seduce Me
Seduce Me is a popular hit single by Tanzanian singer Ali Kiba, known for its catchy Bongo Flava style and romantic lyrics.
|
E1053035
|
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: Seduce Me | Statement: [Ali Kiba, notableWork, Seduce Me]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Seduce Me Context triple: [Ali Kiba, notableWork, Seduce Me]
-
A.
Seduces Me
"Seduces Me" is a romantic pop ballad by Celine Dion featured on her 1996 album "Falling into You."
-
B.
Siduction
Siduction is a Linux distribution derived from Debian, known for its rolling-release model and focus on providing an up-to-date, user-friendly desktop environment.
-
C.
Tempted
"Tempted" is a country music album by American singer-songwriter Marty Stuart, known for its blend of traditional country and rockabilly influences.
-
D.
The Grand Seduction
The Grand Seduction is a 2013 Canadian comedy film about a small fishing village’s elaborate scheme to charm a doctor into staying in their community.
-
E.
A Soft Seduction
"A Soft Seduction" is a song by the American alternative rock band Feelings.
- 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: Seduce Me Triple: [Ali Kiba, notableWork, Seduce Me]
Generated description
Seduce Me is a popular hit single by Tanzanian singer Ali Kiba, known for its catchy Bongo Flava style and romantic lyrics.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Seduce Me Target entity description: Seduce Me is a popular hit single by Tanzanian singer Ali Kiba, known for its catchy Bongo Flava style and romantic lyrics.
-
A.
Seduces Me
"Seduces Me" is a romantic pop ballad by Celine Dion featured on her 1996 album "Falling into You."
-
B.
Siduction
Siduction is a Linux distribution derived from Debian, known for its rolling-release model and focus on providing an up-to-date, user-friendly desktop environment.
-
C.
Tempted
"Tempted" is a country music album by American singer-songwriter Marty Stuart, known for its blend of traditional country and rockabilly influences.
-
D.
The Grand Seduction
The Grand Seduction is a 2013 Canadian comedy film about a small fishing village’s elaborate scheme to charm a doctor into staying in their community.
-
E.
A Soft Seduction
"A Soft Seduction" is a song by the American alternative rock band Feelings.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65aab348190a6611f5765f8392d |
completed | April 12, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78b1222648190a70f50e6e5c34593 |
completed | May 3, 2026, 5:51 p.m. |
| NEDg | Description generation | batch_69f78c0030e481909c20f21ddaa480dc |
completed | May 3, 2026, 5:55 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f78d6d74bc8190ad5476a06e8fd8ad |
completed | May 3, 2026, 6:01 p.m. |
Created at: April 9, 2026, 9:53 p.m.