Triple
T3230806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maria Magdalena Keverich |
E67733
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Magdalena |
E38830
|
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: [Maria Magdalena Keverich, givenName, Magdalena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magdalena Context triple: [Maria Magdalena Keverich, givenName, Magdalena]
-
A.
Magdalena
chosen
Magdalena is the given first name of Swedish opera singer and environmental activist Malena Ernman.
-
B.
Bassein
Bassein is a historic coastal town in western India, now known as Vasai, notable for its strategic port and colonial-era fortifications that played a key role in regional power struggles.
-
C.
Morava
Morava is a Central European river that forms part of the border between Austria, the Czech Republic, and Slovakia before joining the Danube near Bratislava.
-
D.
Ema
Ema is a given name used as a variant spelling of Emma in various languages and cultures.
-
E.
Freirina
Freirina is a small town and commune in northern Chile known for its agricultural activity and historic architecture within the Atacama Region.
- 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_69ad858c61888190a31196310d9b30b5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaeb99e088190a8eeca2ca53707e7 |
completed | March 8, 2026, 5:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2772e3e2081908dec43f8e4a2fb51 |
completed | March 12, 2026, 8:19 a.m. |
Created at: March 8, 2026, 3:08 p.m.