Triple
T9430955
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vanadium |
E227372
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Vanadis |
E359864
|
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: Vanadis | Statement: [Vanadium, namedAfter, Vanadis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vanadis Context triple: [Vanadium, namedAfter, Vanadis]
-
A.
Vanadís
chosen
Vanadís is an epithet of the Norse goddess Freyja, highlighting her role as a prominent deity of the Vanir associated with love, beauty, fertility, and magic.
-
B.
Vallader
Vallader is a major dialect of the Romansh language spoken primarily in Switzerland’s Lower Engadine region and used in local literature and education.
-
C.
Vanth
Vanth is the small, likely captured moon of the distant Kuiper Belt dwarf planet Orcus.
-
D.
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.
-
E.
Velda
Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
- 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_69ca8436ba308190903e470776d2d893 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7e5ed7408190beda5fb078e9345a |
completed | April 1, 2026, 8:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1104033c08190a3670b017bd984d5 |
completed | April 4, 2026, 1:21 p.m. |
Created at: March 30, 2026, 7:49 p.m.