Triple
T7644058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Snow Queen |
E173077
|
entity |
| Predicate | mainProtagonist |
P9202
|
FINISHED |
| Object |
Gerda
Gerda is the brave and devoted young heroine of Hans Christian Andersen’s fairy tale who embarks on a perilous journey to rescue her friend Kai from the Snow Queen.
|
E677904
|
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: Gerda | Statement: [The Snow Queen, mainProtagonist, Gerda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gerda Context triple: [The Snow Queen, mainProtagonist, Gerda]
-
A.
Grete
Grete is the given name of Grete Hermann, a German mathematician and philosopher known for her pioneering work in the foundations of quantum mechanics and computer algebra.
-
B.
Astrid
Astrid is a Belgian princess and member of the country’s royal family.
-
C.
Birgitte
Birgitte is a Danish-born member of the British royal family who holds the title Duchess of Gloucester.
-
D.
Ottilia
Ottilia is a feminine given name of Germanic origin, related to Otto and typically interpreted to mean "wealth" or "prosperity."
-
E.
Helga
Helga is a feminine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
- 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: Gerda Triple: [The Snow Queen, mainProtagonist, Gerda]
Generated description
Gerda is the brave and devoted young heroine of Hans Christian Andersen’s fairy tale who embarks on a perilous journey to rescue her friend Kai from the Snow Queen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gerda Target entity description: Gerda is the brave and devoted young heroine of Hans Christian Andersen’s fairy tale who embarks on a perilous journey to rescue her friend Kai from the Snow Queen.
-
A.
Grete
Grete is the given name of Grete Hermann, a German mathematician and philosopher known for her pioneering work in the foundations of quantum mechanics and computer algebra.
-
B.
Astrid
Astrid is a Belgian princess and member of the country’s royal family.
-
C.
Birgitte
Birgitte is a Danish-born member of the British royal family who holds the title Duchess of Gloucester.
-
D.
Ottilia
Ottilia is a feminine given name of Germanic origin, related to Otto and typically interpreted to mean "wealth" or "prosperity."
-
E.
Helga
Helga is a feminine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6faf13858819095262664e1e04eb7 |
completed | March 27, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c870d510f08190ad7706f582e8c1a0 |
completed | March 29, 2026, 12:22 a.m. |
| NEDg | Description generation | batch_69c87328c2cc81908b9fb89f5fee062e |
completed | March 29, 2026, 12:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c873846a188190a3a1cc56ac247fb0 |
completed | March 29, 2026, 12:34 a.m. |
Created at: March 27, 2026, 3:58 p.m.