Triple
T940997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Anna Custis Lee |
E20304
|
entity |
| Predicate | givenName |
P17
|
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: [Mary Anna Custis Lee, givenName, Mary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Context triple: [Mary Anna Custis Lee, givenName, Mary]
-
A.
Mary
Mary is a minor character in Mark Twain's novel "The Adventures of Tom Sawyer," known as Tom's kind and well-behaved cousin.
-
B.
Mary
Mary is a significant urban and economic center in southeastern Turkmenistan, known for its role in the country’s natural gas and cotton industries.
-
C.
Mary
Mary, Princess Royal and Princess of Orange, was the eldest daughter of King Charles I of England and the wife of William II of Orange, making her a key figure in 17th-century Anglo-Dutch royal relations.
-
D.
Mary
chosen
Mary is a central figure in Christianity, venerated as the mother of Jesus and often honored as the Virgin Mary.
-
E.
Mary
Mary, Princess Royal and Countess of Harewood, was a daughter of King George V and Queen Mary of the United Kingdom and a prominent British royal figure in the early to mid-20th century.
- 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_69a493b0270c81909e6c9ce310f6aa55 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b38cc6888190b1d9043ec8fbcbc3 |
completed | March 1, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac6f023de4819099af23a8d30cb96f |
completed | March 7, 2026, 6:31 p.m. |
Created at: March 1, 2026, 7:40 p.m.