Triple
T20752350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anastasia |
E510756
|
entity |
| Predicate | shortForm |
P43
|
FINISHED |
| Object | Tasia |
—
|
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: Tasia | Statement: [Anastasia, shortForm, Tasia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tasia Context triple: [Anastasia, shortForm, Tasia]
-
A.
Neilia
Neilia was an American educator best known as the first wife of Joe Biden, who tragically died in a car accident in 1972 along with their infant daughter.
-
B.
Tenea
Tenea was an ancient Greek city, traditionally associated with Corinthian colonists and mythic Trojan origins, known from classical sources and archaeological discoveries in the Peloponnese.
-
C.
Juliaetta
Juliaetta is a small rural city in north-central Idaho, known for its agricultural surroundings and location in the Clearwater River region.
-
D.
Kara
chosen
Kara is a feminine given name used in various cultures, often associated with meanings like “beloved,” “friend,” or “pure.”
-
E.
Kara
Kara is a fictional character from the Star Wars universe who hails from the planet Serenno.
- 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_69e0b4c909ec8190b05987f1639513f6 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c22be6588190b137193cb3184fc0 |
completed | April 21, 2026, 12:17 a.m. |
Created at: April 16, 2026, 12:34 p.m.