Triple
T16670336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Velvet Revolver |
E405090
|
entity |
| Predicate | single |
P3283
|
FINISHED |
| Object |
Slither
"Slither" is a hard rock song by the supergroup Velvet Revolver, known for its heavy riffs and as one of the band's most popular tracks.
|
E1226759
|
NE FINISHED |
How this triple was built (4 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: Slither | Statement: [Velvet Revolver, single, Slither]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Slither Context triple: [Velvet Revolver, single, Slither]
-
A.
Slither
Slither is a 2006 horror-comedy film that blends grotesque alien invasion elements with dark humor and cult-movie sensibilities.
-
B.
Slither
Slither is a 1973 American crime-comedy film known for its offbeat humor and ensemble cast, including Louise Lasser and James Caan.
-
C.
Schlangen
Schlangen is a small municipality in the Lippe district of North Rhine-Westphalia, Germany, known for its rural character and proximity to the Teutoburg Forest.
-
D.
Serpenti
Serpenti is Bulgari’s iconic snake-inspired jewelry and watch collection, renowned for its coiling designs and luxurious, glamorous aesthetic.
-
E.
Lagarto
Lagarto is a municipality in the Brazilian state of Sergipe, known for its agricultural activities and growing regional commerce.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Slither Triple: [Velvet Revolver, single, Slither]
Generated description
"Slither" is a hard rock song by the supergroup Velvet Revolver, known for its heavy riffs and as one of the band's most popular tracks.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Slither Target entity description: "Slither" is a hard rock song by the supergroup Velvet Revolver, known for its heavy riffs and as one of the band's most popular tracks.
-
A.
Slither
Slither is a 2006 horror-comedy film that blends grotesque alien invasion elements with dark humor and cult-movie sensibilities.
-
B.
Slither
Slither is a 1973 American crime-comedy film known for its offbeat humor and ensemble cast, including Louise Lasser and James Caan.
-
C.
Schlangen
Schlangen is a small municipality in the Lippe district of North Rhine-Westphalia, Germany, known for its rural character and proximity to the Teutoburg Forest.
-
D.
Serpenti
Serpenti is Bulgari’s iconic snake-inspired jewelry and watch collection, renowned for its coiling designs and luxurious, glamorous aesthetic.
-
E.
Lagarto
Lagarto is a municipality in the Brazilian state of Sergipe, known for its agricultural activities and growing regional commerce.
- F. None of above. chosen
Provenance (5 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37ca079ec819090b356c86a9241cc |
completed | April 18, 2026, 12:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a3692588190a94d349cb63d9749 |
completed | May 10, 2026, 1:37 p.m. |
| NEDg | Description generation | batch_6a008ad087b08190b725382c68687a15 |
completed | May 10, 2026, 1:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a008b9a8b6481909df37edcecdd292c |
completed | May 10, 2026, 1:43 p.m. |
Created at: April 10, 2026, 5:18 a.m.