Triple
T15035839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctor Who: The Tenth Doctor (Titan Comics) |
E378474
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Cindy Wu
Cindy Wu is a companion character in Titan Comics' Doctor Who series who travels with the Tenth Doctor on various adventures.
|
E1132700
|
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: Cindy Wu | Statement: [Doctor Who: The Tenth Doctor (Titan Comics), featuresCharacter, Cindy Wu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cindy Wu Context triple: [Doctor Who: The Tenth Doctor (Titan Comics), featuresCharacter, Cindy Wu]
-
A.
Cindy Cheung
Cindy Cheung is an American actress known for her work in independent films and television, often appearing in character-driven dramas and comedies.
-
B.
Lindsay Wu
Lindsay Wu is a biomedical scientist known for his research on aging and metabolism, particularly in the field of sirtuins and NAD⁺ biology.
-
C.
Cissy Wang
Cissy Wang is a Hong Kong-based model, entrepreneur, and philanthropist best known as the wife and business partner of martial arts star Donnie Yen.
-
D.
Yvonne Chu
Yvonne Chu is the wife of Nobel Prize–winning physicist and former U.S. Secretary of Energy Steven Chu.
-
E.
Vivian Chan
Vivian Chan is a personal name shared by multiple individuals, including professionals in fields such as science, media, and business.
- 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: Cindy Wu Triple: [Doctor Who: The Tenth Doctor (Titan Comics), featuresCharacter, Cindy Wu]
Generated description
Cindy Wu is a companion character in Titan Comics' Doctor Who series who travels with the Tenth Doctor on various adventures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cindy Wu Target entity description: Cindy Wu is a companion character in Titan Comics' Doctor Who series who travels with the Tenth Doctor on various adventures.
-
A.
Cindy Cheung
Cindy Cheung is an American actress known for her work in independent films and television, often appearing in character-driven dramas and comedies.
-
B.
Lindsay Wu
Lindsay Wu is a biomedical scientist known for his research on aging and metabolism, particularly in the field of sirtuins and NAD⁺ biology.
-
C.
Cissy Wang
Cissy Wang is a Hong Kong-based model, entrepreneur, and philanthropist best known as the wife and business partner of martial arts star Donnie Yen.
-
D.
Yvonne Chu
Yvonne Chu is the wife of Nobel Prize–winning physicist and former U.S. Secretary of Energy Steven Chu.
-
E.
Vivian Chan
Vivian Chan is a personal name shared by multiple individuals, including professionals in fields such as science, media, and business.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded82b29948190acda49cbec3f927a |
completed | April 15, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9ddfc13481909333690016650410 |
completed | May 9, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_69fe9e7e12488190972b383d66a2651e |
completed | May 9, 2026, 2:39 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe9f0dd1ac8190a802e9b388b9c770 |
completed | May 9, 2026, 2:42 a.m. |
Created at: April 10, 2026, 2:59 a.m.