Triple
T5317054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claudia Black |
E119176
|
entity |
| Predicate | hasRole |
P161
|
FINISHED |
| Object |
Ma-Sha
Ma-Sha is a character portrayed by actress Claudia Black, best known from her work in science fiction and fantasy television and film.
|
E510466
|
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: Ma-Sha | Statement: [Claudia Black, hasRole, Ma-Sha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ma-Sha Context triple: [Claudia Black, hasRole, Ma-Sha]
-
A.
Haramosh Shina
Haramosh Shina is a regional dialect of the Shina language spoken in the Haramosh area of northern Pakistan.
-
B.
Shinmei
Shinmei is a divine title associated with Emperor Jimmu, the legendary first emperor of Japan revered as a descendant of the sun goddess Amaterasu.
-
C.
Miyabi
Miyabi is a traditional Japanese-inspired lighting theme used on Tokyo Skytree, characterized by elegant, refined color schemes that evoke classical aesthetics.
-
D.
Shiban
Shiban was a Mongol prince of the Golden Horde, a son of Jochi and grandson of Genghis Khan who founded the Shibanid line.
-
E.
Munefusa
Munefusa is the birth name of Matsuo Bashō, the renowned 17th-century Japanese haiku poet and travel writer.
- 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: Ma-Sha Triple: [Claudia Black, hasRole, Ma-Sha]
Generated description
Ma-Sha is a character portrayed by actress Claudia Black, best known from her work in science fiction and fantasy television and film.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ma-Sha Target entity description: Ma-Sha is a character portrayed by actress Claudia Black, best known from her work in science fiction and fantasy television and film.
-
A.
Haramosh Shina
Haramosh Shina is a regional dialect of the Shina language spoken in the Haramosh area of northern Pakistan.
-
B.
Shinmei
Shinmei is a divine title associated with Emperor Jimmu, the legendary first emperor of Japan revered as a descendant of the sun goddess Amaterasu.
-
C.
Miyabi
Miyabi is a traditional Japanese-inspired lighting theme used on Tokyo Skytree, characterized by elegant, refined color schemes that evoke classical aesthetics.
-
D.
Shiban
Shiban was a Mongol prince of the Golden Horde, a son of Jochi and grandson of Genghis Khan who founded the Shibanid line.
-
E.
Munefusa
Munefusa is the birth name of Matsuo Bashō, the renowned 17th-century Japanese haiku poet and travel writer.
- 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_69bd446b57bc8190a513d2e6c40314f3 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd854fd07c8190b4f1c3c8e618c308 |
completed | March 20, 2026, 5:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf1111f104819094d7646dec32fad2 |
completed | March 21, 2026, 9:43 p.m. |
| NEDg | Description generation | batch_69bf11a601c481908a8cb6ea2c04d6df |
completed | March 21, 2026, 9:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf127799208190a47580ed7b9ad550 |
completed | March 21, 2026, 9:49 p.m. |
Created at: March 20, 2026, 1:54 p.m.