Triple
T22103350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brünnhilde |
E546222
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Valkyries |
—
|
NE NERFINISHED |
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: Valkyries | Statement: [Brünnhilde, associatedWith, Valkyries]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valkyries Context triple: [Brünnhilde, associatedWith, Valkyries]
-
A.
Valkyries
chosen
Valkyries are warrior maidens from Norse mythology who serve Odin by choosing those who die in battle and escorting them to the afterlife.
-
B.
Valkyrior
The Valkyrior are an elite all-female Asgardian warrior force in the Marvel Cinematic Universe, renowned for riding winged horses into battle and serving as Odin’s legendary champions.
-
C.
The Valkyries
"The Valkyries" is a mystical, semi-autobiographical novel by Paulo Coelho that follows a spiritual journey through the Mojave Desert exploring themes of faith, love, and self-discovery.
-
D.
Helden
Helden is a town in the Dutch province of Limburg, known as part of the municipality of Peel en Maas.
-
E.
Guerrière
Guerrière was a French warship that took part in the decisive 1827 naval Battle of Navarino during the Greek War of Independence.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f129175a7881909549883f23c53dca |
completed | April 28, 2026, 9:39 p.m. |
Created at: April 16, 2026, 8:30 p.m.