Triple
T9099104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Star Trek: Voyager |
E218104
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object |
Garrett Wang
Garrett Wang is an American actor best known for playing Ensign Harry Kim on the television series Star Trek: Voyager.
|
E778104
|
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: Garrett Wang | Statement: [Star Trek: Voyager, portrayedBy, Garrett Wang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Garrett Wang Context triple: [Star Trek: Voyager, portrayedBy, Garrett Wang]
-
A.
Jonathan Wang
Jonathan Wang is a film producer best known for his work on the acclaimed, genre-bending movie "Everything Everywhere All at Once."
-
B.
Nathan Wang
Nathan Wang is an American composer known for scoring numerous films and television shows, often blending orchestral and contemporary styles.
-
C.
Christopher Chung
Christopher Chung is an actor known for his role in the British spy drama series "Slow Horses."
-
D.
Felix Chong
Felix Chong is a Hong Kong filmmaker best known as the co-writer and co-creator of the acclaimed crime thriller series "Infernal Affairs," which inspired Martin Scorsese’s "The Departed."
-
E.
Daniel Zhang
Daniel Zhang is a Chinese business executive best known for leading Alibaba Group through a major period of global expansion and for creating the Singles’ Day shopping festival.
- 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: Garrett Wang Triple: [Star Trek: Voyager, portrayedBy, Garrett Wang]
Generated description
Garrett Wang is an American actor best known for playing Ensign Harry Kim on the television series Star Trek: Voyager.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Garrett Wang Target entity description: Garrett Wang is an American actor best known for playing Ensign Harry Kim on the television series Star Trek: Voyager.
-
A.
Jonathan Wang
Jonathan Wang is a film producer best known for his work on the acclaimed, genre-bending movie "Everything Everywhere All at Once."
-
B.
Nathan Wang
Nathan Wang is an American composer known for scoring numerous films and television shows, often blending orchestral and contemporary styles.
-
C.
Christopher Chung
Christopher Chung is an actor known for his role in the British spy drama series "Slow Horses."
-
D.
Felix Chong
Felix Chong is a Hong Kong filmmaker best known as the co-writer and co-creator of the acclaimed crime thriller series "Infernal Affairs," which inspired Martin Scorsese’s "The Departed."
-
E.
Daniel Zhang
Daniel Zhang is a Chinese business executive best known for leading Alibaba Group through a major period of global expansion and for creating the Singles’ Day shopping festival.
- 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_69ca83d9844081908e561e367fda6d45 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc9710ac04819096b9c8d3399b9c35 |
completed | April 1, 2026, 3:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d01824ee2081909cc5e6ae33fab2e5 |
completed | April 3, 2026, 7:42 p.m. |
| NEDg | Description generation | batch_69d019666cb08190b66298ff86a7e1af |
completed | April 3, 2026, 7:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d01a700ce48190868d445bde2462dc |
completed | April 3, 2026, 7:52 p.m. |
Created at: March 30, 2026, 7:15 p.m.