Triple
T30633760
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AKB48 |
E779777
|
entity |
| Predicate | hasSisterGroup |
P3457
|
FINISHED |
| Object |
STU48
STU48 is a Japanese female idol group based in the Setouchi region, formed as a sister group of AKB48 and known for its ship-based theater and performances tied to local revitalization.
|
E1924107
|
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: STU48 | Statement: [AKB48, hasSisterGroup, STU48]
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: STU48 Triple: [AKB48, hasSisterGroup, STU48]
Generated description
STU48 is a Japanese female idol group based in the Setouchi region, formed as a sister group of AKB48 and known for its ship-based theater and performances tied to local revitalization.
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_69f224a431548190a44ad9d088dbf91f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fb2f65857481909813ca82f5af38b3 |
completed | May 6, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2863efb21881908d6ebdbeed6decc4 |
completed | June 9, 2026, 7:05 p.m. |
| NEDg | Description generation | batch_6a2864c56f7c8190a58fc3d7c85669ad |
completed | June 9, 2026, 7:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a28653331c08190b467fba620124049 |
completed | June 9, 2026, 7:10 p.m. |
Created at: April 29, 2026, 8:28 p.m.