Triple
T8008774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glitter |
E186429
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Lost In Love |
E579733
|
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: Lost In Love | Statement: [Glitter, hasPart, Lost In Love]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lost In Love Context triple: [Glitter, hasPart, Lost In Love]
-
A.
Lost in Love
"Lost in Love" is a song by the American R&B group New Edition, showcasing their signature harmonies and romantic ballad style.
-
B.
Lost in Love
chosen
"Lost in Love" is a song best known as a soft rock ballad popularized by the Australian duo Air Supply.
-
C.
Still in Love
"Still in Love" is an R&B song by American singer-songwriter Brian McKnight, showcasing his smooth vocals and romantic ballad style.
-
D.
Without Love
"Without Love" is a lively duet-turned-ensemble love song from the musical Hairspray, celebrating young romance and defiance of social barriers.
-
E.
Love Is Gone
"Love Is Gone" is a popular electronic dance track by French DJ and producer David Guetta that helped cement his rise in the international EDM scene.
- 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3d6f76408190a1312369521a187a |
completed | March 31, 2026, 3:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc569e90d48190a1bf1495496017f8 |
completed | March 31, 2026, 11:19 p.m. |
Created at: March 30, 2026, 5:19 p.m.