Triple
T8463680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magda |
E200104
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Magdalena |
E658416
|
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: Magdalena | Statement: [Magda, hasVariant, Magdalena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magdalena Context triple: [Magda, hasVariant, Magdalena]
-
A.
Magdalena
chosen
Magdalena is a historic town in the Mexican state of Jalisco, known for its role in the tequila-producing region and its proximity to agave landscapes and traditional distilleries.
-
B.
Magdalena
Magdalena is the given first name of Swedish opera singer and environmental activist Malena Ernman.
-
C.
Erna
Erna is the given name of Erna Schneider Hoover, an American mathematician and pioneering computer scientist known for revolutionizing telephone switching systems.
-
D.
Maritta
Maritta is a feminine given name, typically considered a variant of names like Marita or Maria used in various European cultures.
-
E.
Mialet
Mialet is a commune in the Gard department of southern France, known for its scenic Cévennes landscape and proximity to notable caves and natural attractions.
- 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_69ca83198c4c8190a337bf717d1813f5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4a39bd48190b72be7e03cff323b |
completed | March 31, 2026, 3:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6cf9368081909cad61cdf6156a0e |
completed | April 2, 2026, 1:19 p.m. |
Created at: March 30, 2026, 6:10 p.m.