Triple
T18650948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christel Takigawa |
E455933
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Christel
Christel is a feminine given name used in various European and international contexts, often as a variant of Christelle or Christa.
|
E1335978
|
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: Christel | Statement: [Christel Takigawa, givenName, Christel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christel Context triple: [Christel Takigawa, givenName, Christel]
-
A.
Christianne
Christianne is a feminine given name of Latin origin, commonly used in German- and English-speaking countries.
-
B.
Christa
Christa was the first name of Christa McAuliffe, the American teacher and astronaut selected as the first private citizen to fly in space.
-
C.
Charlène
Charlène is a French feminine given name, typically considered a variant of Charlene or a diminutive of Charlotte.
-
D.
Christiane
Christiane is the given name of Christiane Nüsslein-Volhard, the Nobel Prize–winning German developmental biologist known for her pioneering work on genetic control of embryonic development.
-
E.
Therese
Therese is a feminine given name of French origin, commonly associated with Christian saints and used in various European cultures.
- 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: Christel Triple: [Christel Takigawa, givenName, Christel]
Generated description
Christel is a feminine given name used in various European and international contexts, often as a variant of Christelle or Christa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Christel Target entity description: Christel is a feminine given name used in various European and international contexts, often as a variant of Christelle or Christa.
-
A.
Christianne
Christianne is a feminine given name of Latin origin, commonly used in German- and English-speaking countries.
-
B.
Christa
Christa was the first name of Christa McAuliffe, the American teacher and astronaut selected as the first private citizen to fly in space.
-
C.
Charlène
Charlène is a French feminine given name, typically considered a variant of Charlene or a diminutive of Charlotte.
-
D.
Christiane
Christiane is the given name of Christiane Nüsslein-Volhard, the Nobel Prize–winning German developmental biologist known for her pioneering work on genetic control of embryonic development.
-
E.
Therese
Therese is a feminine given name of French origin, commonly associated with Christian saints and used in various European cultures.
- 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_69d8d38ea1e88190997e9b231190ba6f |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55010d27c8190aad8d3c9e8cd31b2 |
completed | April 19, 2026, 9:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05171ec7708190be7531acb3a265cc |
completed | May 14, 2026, 12:28 a.m. |
| NEDg | Description generation | batch_6a05182b38848190ad50785ba1a884ea |
completed | May 14, 2026, 12:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0518e6358c8190ac5f67300d63f852 |
completed | May 14, 2026, 12:35 a.m. |
Created at: April 10, 2026, 11:47 a.m.