Triple
T14815687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gilgiti Shina |
E348307
|
entity |
| Predicate | closelyRelatedTo |
P37
|
FINISHED |
| Object | Astori Shina |
E318535
|
NE FINISHED |
How this triple was built (2 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: Astori Shina | Statement: [Gilgiti Shina, closelyRelatedTo, Astori Shina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Astori Shina Context triple: [Gilgiti Shina, closelyRelatedTo, Astori Shina]
-
A.
Astori Shina
chosen
Astori Shina is a specific dialectal variety associated with the Shina language.
-
B.
Haramosh Shina
Haramosh Shina is a regional dialect of the Shina language spoken in the Haramosh area of northern Pakistan.
-
C.
Inori
Inori is a large-scale 1974–1977 composition by Karlheinz Stockhausen that combines orchestra and a soloist performing stylized ritual gestures, exploring the fusion of music and prayer.
-
D.
Leo Shuken
Leo Shuken was an American film composer and orchestrator known for his work on numerous Hollywood scores during the mid-20th century.
-
E.
Mao Asada
Mao Asada is a retired Japanese figure skater renowned for her triple Axel, multiple World Championship titles, and status as one of the sport’s most influential athletes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe0e89c81908c0e1fe2bc3ebcfc |
completed | April 14, 2026, 11:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe389598848190ba15e6eea2ba2903 |
completed | May 8, 2026, 7:25 p.m. |
Created at: April 10, 2026, 1:49 a.m.