Triple
T13351216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Velma Dinkley |
E318071
|
entity |
| Predicate | voiceActedBy |
P39669
|
FINISHED |
| Object |
Christina Lange
Christina Lange is a voice actress known for portraying the character Velma Dinkley in Scooby-Doo media.
|
E1037909
|
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: Christina Lange | Statement: [Velma Dinkley, voiceActedBy, Christina Lange]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christina Lange Context triple: [Velma Dinkley, voiceActedBy, Christina Lange]
-
A.
Christine Olsen
Christine Olsen is an Australian film producer best known for her work on the acclaimed drama "Rabbit-Proof Fence."
-
B.
Christianne Jensen
Christianne Jensen is a vocalist known for her guest appearance on Jon Bellion’s album "Glory Sound Prep."
-
C.
Tina Christensen
Tina Christensen is a Danish film editor and translator known for her work subtitling and editing a wide range of international films.
-
D.
Beth Johanssen
Beth Johanssen is a brilliant young NASA systems operator and communications specialist who is part of the Ares 3 crew in Andy Weir’s science fiction novel "The Martian."
-
E.
Nina Kristensen
Nina Kristensen is a video game developer and co-founder of the British studio Ninja Theory, known for cinematic action titles like Heavenly Sword and Hellblade: Senua’s Sacrifice.
- 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: Christina Lange Triple: [Velma Dinkley, voiceActedBy, Christina Lange]
Generated description
Christina Lange is a voice actress known for portraying the character Velma Dinkley in Scooby-Doo media.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Christina Lange Target entity description: Christina Lange is a voice actress known for portraying the character Velma Dinkley in Scooby-Doo media.
-
A.
Christine Olsen
Christine Olsen is an Australian film producer best known for her work on the acclaimed drama "Rabbit-Proof Fence."
-
B.
Christianne Jensen
Christianne Jensen is a vocalist known for her guest appearance on Jon Bellion’s album "Glory Sound Prep."
-
C.
Tina Christensen
Tina Christensen is a Danish film editor and translator known for her work subtitling and editing a wide range of international films.
-
D.
Beth Johanssen
Beth Johanssen is a brilliant young NASA systems operator and communications specialist who is part of the Ares 3 crew in Andy Weir’s science fiction novel "The Martian."
-
E.
Nina Kristensen
Nina Kristensen is a video game developer and co-founder of the British studio Ninja Theory, known for cinematic action titles like Heavenly Sword and Hellblade: Senua’s Sacrifice.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99e8c2f1c819094f0970f35f18afa |
completed | April 11, 2026, 1:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7306668288190ae8dc05ebadb4975 |
completed | May 3, 2026, 11:24 a.m. |
| NEDg | Description generation | batch_69f730db3664819095b92fbd369f732b |
completed | May 3, 2026, 11:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7315346508190a3d8d075c7681f6f |
completed | May 3, 2026, 11:28 a.m. |
Created at: April 9, 2026, 9:31 p.m.