Triple
T9110324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Have Nothing |
E218582
|
entity |
| Predicate | followedBySingle |
P134
|
FINISHED |
| Object | Run to You |
E319126
|
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: Run to You | Statement: [I Have Nothing, followedBySingle, Run to You]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Run to You Context triple: [I Have Nothing, followedBySingle, Run to You]
-
A.
Run to You
"Run to You" is a 1984 rock song by Canadian singer-songwriter Bryan Adams, known for its driving guitar riff and status as one of his signature hits.
-
B.
Run to You
chosen
"Run to You" is a 1993 power ballad by Whitney Houston, known for its emotional vocal performance and inclusion on The Bodyguard film soundtrack.
-
C.
Always Run to You
"Always Run to You" is a hard rock song by Bon Jovi from their 1985 album 7800° Fahrenheit.
-
D.
Run to Me
"Run to Me" is a 1972 soft rock ballad by the Bee Gees, known for its lush harmonies and heartfelt lyrics.
-
E.
Where You Gonna Run
"Where You Gonna Run" is a reggae track by South African singer and activist Miriam Makeba, featured on her album "Mama Africa."
- 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_69ca83dc94ac8190b9ef42684d36ff39 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca847102881908f9d86ce9883fb1a |
completed | April 1, 2026, 5:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d03038dba48190991cb76576349bc3 |
completed | April 3, 2026, 9:25 p.m. |
Created at: March 30, 2026, 7:16 p.m.