Triple
T4837444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marija |
E108095
|
entity |
| Predicate | equivalentFormOf |
P6530
|
FINISHED |
| Object | Mary |
E14130
|
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: Mary | Statement: [Marija, equivalentFormOf, Mary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Context triple: [Marija, equivalentFormOf, Mary]
-
A.
Mary
chosen
Mary is a central figure in Christianity, venerated as the mother of Jesus and often honored as the Virgin Mary.
-
B.
Mary
Mary is the given first name of Margaret Truman, the daughter of U.S. President Harry S. Truman and a noted author and singer.
-
C.
Mary
Mary is the given name of the American suspense novelist Mary Higgins Clark, known for her bestselling mystery and thriller books.
-
D.
Mary
Mary is the middle name of Katherine Mary Dewar, a component of her full personal name.
-
E.
Mary
Mary Allerton was a Mayflower passenger and one of the early settlers of Plymouth Colony in 17th-century New England.
- 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_69bd43fbe444819085cb970706ef73f7 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ce193488190a618250a5681f3ff |
completed | March 20, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be67d449188190a2f02fa30aee4891 |
completed | March 21, 2026, 9:41 a.m. |
Created at: March 20, 2026, 1:25 p.m.