Triple
T29100840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shin Megami Tensei |
E736635
|
entity |
| Predicate | hasSpinOff |
P7226
|
FINISHED |
| Object |
Majin Tensei
Majin Tensei is a tactical role-playing game spin-off series of the Shin Megami Tensei franchise, featuring demon summoning and strategic grid-based battles.
|
E1850787
|
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: Majin Tensei | Statement: [Shin Megami Tensei, hasSpinOff, Majin Tensei]
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: Majin Tensei Triple: [Shin Megami Tensei, hasSpinOff, Majin Tensei]
Generated description
Majin Tensei is a tactical role-playing game spin-off series of the Shin Megami Tensei franchise, featuring demon summoning and strategic grid-based battles.
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_69f077ec765c81909474c88bcc8bab43 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f661b58ac48190907b6c6e9ccc2c59 |
completed | May 2, 2026, 8:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2537b8df3c8190b138ae96e4ef85c7 |
completed | June 7, 2026, 9:19 a.m. |
| NEDg | Description generation | batch_6a2542e78e108190a7ead54421361eab |
completed | June 7, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a254363ba088190b6f0b18f68d43add |
completed | June 7, 2026, 10:09 a.m. |
Created at: April 28, 2026, 11:12 a.m.