Triple
T6598599
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Nathan Oliver |
E148538
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Snake Rag |
E146856
|
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: Snake Rag | Statement: [Joseph Nathan Oliver, notableWork, Snake Rag]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Snake Rag Context triple: [Joseph Nathan Oliver, notableWork, Snake Rag]
-
A.
Snake Rag
chosen
"Snake Rag" is a classic early jazz composition by King Oliver, celebrated for its intricate ensemble breaks and as a key example of New Orleans–style jazz.
-
B.
Constrictor
Constrictor is a water slide attraction at Wet'n'Wild Gold Coast known for its tight twists and high-speed tube-style turns.
-
C.
Snake
"Snake" is a raw, intense track by PJ Harvey from her critically acclaimed 1993 album "Rid of Me."
-
D.
Basilisk
The Basilisk is a gigantic, deadly serpent from the Harry Potter series whose gaze can kill and whose venom is among the most lethal magical substances.
-
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.
- 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_69c687e7b8688190811ffee72e096468 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6aeeffdf0819090af7bba918bef84 |
completed | March 27, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e43224dc81909dea493a5ee2726e |
completed | March 27, 2026, 8:10 p.m. |
Created at: March 27, 2026, 1:56 p.m.