Triple
T6500849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marié |
E148882
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Mary |
unclear NED1
|
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: [Marié, relatedName, Mary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Context triple: [Marié, relatedName, Mary]
-
A.
Mary
Mary is the given first name of the acclaimed American actress Meryl Streep.
-
B.
Mary
Mary Eleanor Darwin was a member of the Darwin family, known primarily as a descendant of the naturalist Charles Darwin.
-
C.
Mary
Mary I of England was the 16th-century Queen of England and Ireland best known for her attempt to restore Roman Catholicism and for the Marian persecutions that earned her the nickname "Bloody Mary."
-
D.
Mary
Mary is a studio album by Ghanaian rapper Sarkodie, known for its highlife influences and tribute to his late grandmother.
-
E.
Mary
Mary is the first name of American soccer legend Abby Wambach, one of the most prolific goal scorers in international women’s football.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69c687e9ad288190bae5bcac9c8ac855 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c68ad2e148819088be5c48ad73dc59 |
completed | March 27, 2026, 1:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6e40c193c8190b4d7acd4530121f0 |
completed | March 27, 2026, 8:09 p.m. |
Created at: March 27, 2026, 1:42 p.m.