Triple
T5156390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RC6 |
E116319
|
entity |
| Predicate | competedWith |
P1375
|
FINISHED |
| Object | Serpent |
E368195
|
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: Serpent | Statement: [RC6, competedWith, Serpent]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serpent Context triple: [RC6, competedWith, Serpent]
-
A.
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.
-
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.
World Serpent
chosen
The World Serpent is a colossal sea serpent from Norse mythology that encircles the earth and is fated to battle Thor during Ragnarök.
-
D.
Nagini
Nagini is Voldemort’s loyal giant snake in the Harry Potter series, later revealed to be a cursed Maledictus and a key part of his dark power.
-
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_69bd445d94788190b72e2cc563120995 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79019c6481909641f173c5b3769a |
completed | March 20, 2026, 4:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bed0123bc48190920f60fc29f64734 |
completed | March 21, 2026, 5:06 p.m. |
Created at: March 20, 2026, 1:44 p.m.