Triple
T38511948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 辰野金吾 |
E921934
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object |
伊予国宇摩郡川之江村
伊予国宇摩郡川之江村は、現在の愛媛県東予地方にあたる旧伊予国宇摩郡に属した村で、近代日本を代表する建築家・辰野金吾の出身地として知られる。
|
E2140513
|
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: 伊予国宇摩郡川之江村 | Statement: [辰野金吾, birthPlace, 伊予国宇摩郡川之江村]
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: 伊予国宇摩郡川之江村 Triple: [辰野金吾, birthPlace, 伊予国宇摩郡川之江村]
Generated description
伊予国宇摩郡川之江村は、現在の愛媛県東予地方にあたる旧伊予国宇摩郡に属した村で、近代日本を代表する建築家・辰野金吾の出身地として知られる。
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_69f76ea3c5448190aa7002fc1ba3f874 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcd28d33b08190a0f6ff47be5eaaae |
completed | May 7, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a41d6620d68819092a48ef180055be4 |
completed | June 29, 2026, 2:20 a.m. |
| NEDg | Description generation | batch_6a41db13f8d88190a5be321217369ee5 |
completed | June 29, 2026, 2:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a41dba5b784819093a5c975762bf095 |
completed | June 29, 2026, 2:42 a.m. |
Created at: May 3, 2026, 4:32 p.m.