Triple
T9058178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | You Give Love a Bad Name |
E217056
|
entity |
| Predicate | drummer |
P15280
|
FINISHED |
| Object | Tico Torres |
E302503
|
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: Tico Torres | Statement: [You Give Love a Bad Name, drummer, Tico Torres]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tico Torres Context triple: [You Give Love a Bad Name, drummer, Tico Torres]
-
A.
Tico Torres
chosen
Tico Torres is an American drummer best known as the longtime percussionist for the rock band Bon Jovi.
-
B.
Carlos Rios
Carlos Rios is a music producer best known for his work on the hit album "Can't Slow Down."
-
C.
Carlos Rios
Carlos Rios is a songwriter best known for co-writing the hit song "Dancing on the Ceiling."
-
D.
Carlos Torres
Carlos Torres is the fun-loving, rule-bending father in the family comedy film "Yes Day," whose agreement to grant his kids' every request for 24 hours drives the movie's chaotic and heartfelt adventures.
-
E.
Héctor Vivanco
Héctor Vivanco is a notable individual recognized for achievements significant enough to be associated with the surname Vivanco.
- 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_69ca83d4425481909a319dab847724ec |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7ec808bc8190957b80820d98fd5b |
completed | April 1, 2026, 2:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1c3f31db48190a63d0d60f108496f |
completed | April 5, 2026, 2:07 a.m. |
Created at: March 30, 2026, 7:10 p.m.