Triple
T21938073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lou-lan |
E541745
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Kroraina |
—
|
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: Kroraina | Statement: [Lou-lan, hasAlternativeName, Kroraina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kroraina Context triple: [Lou-lan, hasAlternativeName, Kroraina]
-
A.
Kroraina
chosen
Kroraina was an ancient Central Asian oasis kingdom in the Tarim Basin, known from Chinese records as Shanshan and important along the Silk Road.
-
B.
Drasna
Drasna is a Dragon-type specialist who serves as one of the Elite Four members in the Kalos region of the Pokémon series.
-
C.
Klyntar
Klyntar are an alien symbiote species in Marvel Comics known for bonding with hosts to enhance their abilities while often exerting a corrupting influence.
-
D.
Wadska
Wadska is a central character in the series "Good Vibes," known for his laid-back, comedic personality within the show's ensemble cast.
-
E.
Krakhuna
Krakhuna is a Georgian white grape variety from the Imereti region, known for producing aromatic, full-bodied wines with pronounced acidity.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1241e35bc81909eb3225d5cd97b92 |
completed | April 28, 2026, 9:18 p.m. |
Created at: April 16, 2026, 7:55 p.m.