Triple
T23075657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anneliese Maier |
E575322
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Anneliese
Anneliese is a feminine given name of German origin, commonly used in German-speaking countries and derived from a combination of Anna and Liese (a form of Elisabeth).
|
E1569667
|
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: Anneliese | Statement: [Anneliese Maier, givenName, Anneliese]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anneliese Context triple: [Anneliese Maier, givenName, Anneliese]
-
A.
Annelies
Annelies is the given first name of Anne Frank, the Jewish diarist whose writings from hiding during the Holocaust became world-famous.
-
B.
Anneliese Judge
Anneliese Judge is an American actress best known for her role as Annie Sullivan in the Netflix drama series "Sweet Magnolias."
-
C.
Emeline
Emeline is a feminine given name of French origin, historically used in English-speaking countries.
-
D.
Annis
Annis is a feminine given name of English origin, historically used in the Anglophone world.
-
E.
Ernestine
Ernestine is the given first name of the American actress and sex symbol Jane Russell, known for her roles in classic Hollywood films of the 1940s and 1950s.
- 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: Anneliese Triple: [Anneliese Maier, givenName, Anneliese]
Generated description
Anneliese is a feminine given name of German origin, commonly used in German-speaking countries and derived from a combination of Anna and Liese (a form of Elisabeth).
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anneliese Target entity description: Anneliese is a feminine given name of German origin, commonly used in German-speaking countries and derived from a combination of Anna and Liese (a form of Elisabeth).
-
A.
Annelies
Annelies is the given first name of Anne Frank, the Jewish diarist whose writings from hiding during the Holocaust became world-famous.
-
B.
Anneliese Judge
Anneliese Judge is an American actress best known for her role as Annie Sullivan in the Netflix drama series "Sweet Magnolias."
-
C.
Emeline
Emeline is a feminine given name of French origin, historically used in English-speaking countries.
-
D.
Annis
Annis is a feminine given name of English origin, historically used in the Anglophone world.
-
E.
Ernestine
Ernestine is the given first name of the American actress and sex symbol Jane Russell, known for her roles in classic Hollywood films of the 1940s and 1950s.
- 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_69e245be28d48190ad1348d5a73db37d |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18c62c200819099c92654493288ad |
completed | April 29, 2026, 4:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c15acfcb48190a4131dc8c6c76f02 |
completed | May 19, 2026, 7:47 a.m. |
| NEDg | Description generation | batch_6a0c16bea8b881908bc202005408f806 |
completed | May 19, 2026, 7:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c17da6a108190b37d1e69e6f24e00 |
completed | May 19, 2026, 7:57 a.m. |
Created at: April 17, 2026, 3:56 p.m.