Triple
T28997620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susukino |
E736208
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object |
Odori area of Sapporo
The Odori area of Sapporo is the central downtown district of the city, known for Odori Park, major shopping and business streets, and as a main venue for events like the Sapporo Snow Festival.
|
E1845099
|
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: Odori area of Sapporo | Statement: [Susukino, near, Odori area of Sapporo]
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: Odori area of Sapporo Triple: [Susukino, near, Odori area of Sapporo]
Generated description
The Odori area of Sapporo is the central downtown district of the city, known for Odori Park, major shopping and business streets, and as a main venue for events like the Sapporo Snow Festival.
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_69f077eacd0481908ef0bafd74491cd0 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f65fb8003081909d0e3ee34237bc29 |
completed | May 2, 2026, 8:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a2505bc2c408190a00aa2ac202c7eeb |
completed | June 7, 2026, 5:46 a.m. |
| NEDg | Description generation | batch_6a2509d511b481908fb354a22e7ee542 |
completed | June 7, 2026, 6:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a250e35cb2c81909d7632be22680434 |
completed | June 7, 2026, 6:22 a.m. |
Created at: April 28, 2026, 9:32 a.m.