Triple
T22578619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love Language |
E544498
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | Love Language |
—
|
NE NERFINISHED |
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: Love Language | Statement: [Love Language, title, Love Language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Love Language Context triple: [Love Language, title, Love Language]
-
A.
Love Language
chosen
"Love Language" is a song by the American rapper Train of Thought.
-
B.
Love and Affection
"Love and Affection" is a soulful R&B ballad by Sheena Easton, noted for its smooth production and emotive vocal performance.
-
C.
Love
Love is an American professional basketball player known for his elite rebounding, three-point shooting, and key role in the Cleveland Cavaliers’ 2016 NBA championship.
-
D.
Love
"Love" is a smooth, neo-soul R&B song by Musiq Soulchild that became one of his signature hits in the early 2000s.
-
E.
Love
Love is a complex and multifaceted human emotion characterized by deep affection, attachment, and care for others.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e30d05481909df915354c89f0d6 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f15feee27c8190b31c923e1f00a363 |
completed | April 29, 2026, 1:33 a.m. |
Created at: April 16, 2026, 8:53 p.m.