Triple
T17694929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Das Bergwerk zu Falun |
E441136
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Anna
Anna is a central female character in E.T.A. Hoffmann’s Romantic tale "Das Bergwerk zu Falun," embodying love, fate, and the tension between earthly life and mystical destiny.
|
E1282454
|
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: [Das Bergwerk zu Falun, hasCharacter, Anna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Context triple: [Das Bergwerk zu Falun, hasCharacter, 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 key female resistance fighter in the World War II adventure film "The Guns of Navarone," whose complex loyalties and actions significantly impact the mission’s outcome.
-
C.
Anna
Anna is a small city in north-central Texas that forms part of the fast-growing suburban region north of Dallas.
-
D.
Anna
Anna is a biblical figure in the Book of Tobit, known as Tobit's wife and the mother of Tobias.
-
E.
Anna
Anna is the given first name of the American actress, comedian, and director Nancy Walker.
- 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: [Das Bergwerk zu Falun, hasCharacter, Anna]
Generated description
Anna is a central female character in E.T.A. Hoffmann’s Romantic tale "Das Bergwerk zu Falun," embodying love, fate, and the tension between earthly life and mystical destiny.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anna Target entity description: Anna is a central female character in E.T.A. Hoffmann’s Romantic tale "Das Bergwerk zu Falun," embodying love, fate, and the tension between earthly life and mystical destiny.
-
A.
Anna
Anna is the central protagonist of Arnold Bennett’s novel "Anna of the Five Towns," a young woman navigating love, duty, and religious constraint in an industrial English setting.
-
B.
Anna
Anna is a character in Giacomo Puccini's early opera-ballet *Le Villi*, which blends elements of romance and the supernatural.
-
C.
Anna
Anna is the tragic, aristocratic heroine of Leo Tolstoy’s novel "Anna Karenina," whose passionate affair and struggle against societal norms lead to her downfall.
-
D.
Anna
Anna is a central fictional character in Michael Ondaatje's novel "Divisadero," around whom much of the story's emotional and narrative complexity revolves.
-
E.
Anna
Anna is a curious and adventurous character known for journeying into the magical Enchanted Forest.
- F. None of above. chosen
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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e471559744819080b99081c90ab614 |
completed | April 19, 2026, 6:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a022327dbf8819083cc9366ddcf3ed2 |
completed | May 11, 2026, 6:42 p.m. |
| NEDg | Description generation | batch_6a02245658108190ab50ffb98eef589b |
completed | May 11, 2026, 6:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0224c554788190ae1aa7d4e7211aaf |
completed | May 11, 2026, 6:49 p.m. |
Created at: April 10, 2026, 10:04 a.m.