Triple
T13944884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anne Bancroft |
E335354
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Anne
Anne is a feminine given name of Hebrew origin, commonly used in English-speaking countries and associated with numerous historical and cultural figures.
|
E267026
|
NE FINISHED |
How this triple was built (4 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 Bancroft, givenName, Anne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anne Context triple: [Anne Bancroft, givenName, Anne]
-
A.
Anne
Anne is the birth name of Nancy Reagan, the former First Lady of the United States and wife of President Ronald Reagan.
-
B.
Anne
Anne is the protagonist of "The Darkest Hour," around whom the film’s central conflict and emotional journey revolve.
-
C.
Anne
Anne was the ship on which the 17th-century English sailor and later Ceylon captive Robert Knox served during his voyages.
-
D.
Anne
Anne of Palatinate-Simmern was a 16th-century German noblewoman from the House of Wittelsbach who became Electress Palatine through marriage to Elector Frederick III.
-
E.
Anne
Anne is traditionally revered in Christian tradition as the mother of the Virgin Mary and the grandmother of Jesus.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Anne Triple: [Anne Bancroft, givenName, Anne]
Generated description
Anne is a feminine given name of Hebrew origin, commonly used in English-speaking countries and associated with numerous historical and cultural figures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anne Target entity description: Anne is a feminine given name of Hebrew origin, commonly used in English-speaking countries and associated with numerous historical and cultural figures.
-
A.
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.
-
B.
Anne
Anne is the given name of Anne Morrow Lindbergh, the American author and aviator who was married to famed aviator Charles Lindbergh.
-
C.
Anne
Anne is the given name of Anne Hilarion de Costentin de Tourville, a renowned French naval commander of the late 17th and early 18th centuries.
-
D.
Anne
Anne is the middle name of Loretta Anne Rogers, a prominent Canadian businesswoman and philanthropist associated with the Rogers telecommunications family.
-
E.
Anne
Anne is the given name of Lady Lucy Anne FitzGerald, an Irish noblewoman of the late 18th and early 19th centuries known for her connections to the United Irishmen movement.
- F. None of above.
Provenance (5 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e10f60c81908ee9636e85c070ff |
completed | April 14, 2026, 12:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1ca49a881909e77b5a2ae13265f |
completed | May 6, 2026, 8:17 p.m. |
| NEDg | Description generation | batch_69fba6e596a081909843ea5173e60af4 |
completed | May 6, 2026, 8:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fba74fe350819080eee658bca7eaf0 |
completed | May 6, 2026, 8:40 p.m. |
Created at: April 9, 2026, 10:17 p.m.