Triple
T13939340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Go Deep |
E335197
|
entity |
| Predicate | follows |
P134
|
FINISHED |
| Object | I Get Lonely |
E335196
|
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: I Get Lonely | Statement: [Go Deep, follows, I Get Lonely]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: I Get Lonely Context triple: [Go Deep, follows, I Get Lonely]
-
A.
I Get Lonely
chosen
"I Get Lonely" is a sultry R&B song by Janet Jackson, released as a single from her 1997 album *The Velvet Rope* and known for its smooth production and themes of longing and intimacy.
-
B.
So Lonely
"So Lonely" is a 1978 reggae-influenced rock song by the British band The Police, known for its catchy melody and themes of isolation and heartache.
-
C.
Too Lonely
"Too Lonely" is a song by the artist Ytilaer, likely reflecting themes of isolation and emotional vulnerability.
-
D.
Only Lonely
"Only Lonely" is a 1985 hard rock song by Bon Jovi from their second album, 7800° Fahrenheit.
-
E.
Let Me Be Lonely
"Let Me Be Lonely" is a song by Dionne Warwick that appeared as the B-side to her 1968 hit single "Do You Know the Way to San Jose."
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf5cc8c8190bea74291702b2925 |
completed | April 14, 2026, 12:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce89d2348190b5a50376c2b8248c |
completed | May 3, 2026, 10:39 p.m. |
Created at: April 9, 2026, 10:17 p.m.