Triple
T3599291
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne Browne |
E76215
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Anne |
E267026
|
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: Anne | Statement: [Anne Browne, givenName, Anne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anne Context triple: [Anne Browne, givenName, Anne]
-
A.
Anne
Anne is traditionally revered in Christian tradition as the mother of the Virgin Mary and the grandmother of Jesus.
-
B.
Anne
Anne is the birth name of Nancy Reagan, the former First Lady of the United States and wife of President Ronald Reagan.
-
C.
Anne
Anne was the Queen of Great Britain and Ireland from 1702 to 1714, the last monarch of the House of Stuart.
-
D.
Anne
chosen
Anne is a female given name of Hebrew origin, commonly used in many European languages and historically borne by numerous queens, saints, and notable women.
-
E.
Anne
Anne is the given name of Anne Morrow Lindbergh, the American author and aviator who was married to famed aviator Charles Lindbergh.
- 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_69ad85d93dcc819094fba90cf70f4996 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc19e9e98819094455cb3c4efcb9a |
completed | March 8, 2026, 6:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b43309a9b48190bc2aa6f970d45612 |
completed | March 13, 2026, 3:53 p.m. |
Created at: March 8, 2026, 3:22 p.m.