Triple
T7867840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna d’Este |
E182661
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Anna
Anna is a feminine given name of Hebrew origin meaning "grace" or "favor," widely used across many cultures and languages.
|
E161036
|
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: Anna | Statement: [Anna d’Este, givenName, Anna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Context triple: [Anna d’Este, givenName, Anna]
-
A.
Anna
Anna is the given name of Anna Murray Douglass, an African American abolitionist and the first wife of Frederick Douglass.
-
B.
Anna
Anna is a central female character in the comedy Western film "A Million Ways to Die in the West," portrayed as a sharp-shooting, quick-witted woman who helps the protagonist toughen up in the dangerous frontier.
-
C.
Anna
Anna is the given name of pioneering Chinese American actress Anna May Wong, a trailblazing early Hollywood star and fashion icon.
-
D.
Anna
Anna is a character from the video game "Surfacing," likely serving as a key figure in the game's narrative or player interactions.
-
E.
Anna
Anna is a spirited and optimistic princess from Disney's animated film "Frozen," known for her bravery, loyalty, and deep love for her sister Elsa.
- 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: Anna Triple: [Anna d’Este, givenName, Anna]
Generated description
Anna is a feminine given name of Hebrew origin meaning "grace" or "favor," widely used across many cultures and languages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anna Target entity description: Anna is a feminine given name of Hebrew origin meaning "grace" or "favor," widely used across many cultures and languages.
-
A.
Anna
chosen
Anna is a feminine given name of Hebrew origin meaning "grace" or "favor," widely used across many cultures and languages.
-
B.
Anna
Anna is the given first name of Eleanor Roosevelt, the influential former First Lady of the United States and human rights advocate.
-
C.
Anna
Anna is the given first name of Pauli Murray, the pioneering American civil rights activist, lawyer, and Episcopal priest.
-
D.
Anna
Anna is the given name of Anna Laetitia Barbauld, an influential 18th–19th century English poet, essayist, and children's author.
-
E.
Anna
Anna is traditionally revered in Christianity as the mother of the Virgin Mary and the grandmother of Jesus.
- 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_69ca82894d9081908a832bfce71a4714 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3847c7fc819098e32b6548943da7 |
completed | March 31, 2026, 2:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5b60b3b08190832837bacb8ce965 |
completed | March 31, 2026, 5:28 a.m. |
| NEDg | Description generation | batch_69cb7630b8908190a0b8f4856bceea0a |
completed | March 31, 2026, 7:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cbbfb894588190971ade076acdbd5c |
completed | March 31, 2026, 12:36 p.m. |
Created at: March 30, 2026, 4:55 p.m.