Triple
T28997397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sapporo Lilac Festival Odori venue |
E736204
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object |
Sapporo Lilac Festival
The Sapporo Lilac Festival is an annual spring event in Sapporo, Japan, celebrating the blooming of lilacs with flower displays, food stalls, music, and cultural activities in city parks.
|
E1845096
|
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: Sapporo Lilac Festival | Statement: [Sapporo Lilac Festival Odori venue, partOf, Sapporo Lilac Festival]
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: Sapporo Lilac Festival Triple: [Sapporo Lilac Festival Odori venue, partOf, Sapporo Lilac Festival]
Generated description
The Sapporo Lilac Festival is an annual spring event in Sapporo, Japan, celebrating the blooming of lilacs with flower displays, food stalls, music, and cultural activities in city parks.
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_69f65fb6ef4881909a758c3538fdec03 |
completed | May 2, 2026, 8:33 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.