Triple
T14990639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexa |
E373824
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Alexandrina |
E140338
|
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: Alexandrina | Statement: [Alexa, relatedName, Alexandrina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alexandrina Context triple: [Alexa, relatedName, Alexandrina]
-
A.
Alexandrina
chosen
Alexandrina was the first given name of Queen Victoria, the long-reigning 19th-century British monarch.
-
B.
Victorias
Victorias is a city in the Philippine province of Negros Occidental known for its sugar industry and historic Victorias Milling Company.
-
C.
Lucyana
Lucyana is a feminine given name, typically considered a variant spelling of Luciana and related names like Lucía and Lucy.
-
D.
Elisabeth
Elisabeth is a feminine given name of Hebrew origin, commonly used in various European languages as a form of Elizabeth.
-
E.
Elisabeth
Elisabeth is a metro station on the Brussels Metro system in Brussels, Belgium.
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded715db408190b44e8a8452c79764 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe969683348190bb4688f24227af88 |
completed | May 9, 2026, 2:06 a.m. |
Created at: April 10, 2026, 2:53 a.m.