Triple
T25252912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hanapepe |
E632790
|
entity |
| Predicate | hasCulturalEvent |
P2955
|
FINISHED |
| Object |
Friday Night Art Walk
Friday Night Art Walk is a weekly evening street festival in Hanapepe, Kauai, featuring local art galleries, live music, food vendors, and community gatherings.
|
E1672497
|
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: Friday Night Art Walk | Statement: [Hanapepe, hasCulturalEvent, Friday Night Art Walk]
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: Friday Night Art Walk Triple: [Hanapepe, hasCulturalEvent, Friday Night Art Walk]
Generated description
Friday Night Art Walk is a weekly evening street festival in Hanapepe, Kauai, featuring local art galleries, live music, food vendors, and community gatherings.
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_69e75a8fdd3881909ba0b05aa5da92a7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f4808cf89881909c7d9ee9c42216c4 |
completed | May 1, 2026, 10:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1067ed6b408190861abb62144a50f5 |
completed | May 22, 2026, 2:27 p.m. |
| NEDg | Description generation | batch_6a1068ad981081908f324aa1d7cc5bb2 |
completed | May 22, 2026, 2:31 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a106a0c2d7881908ca2ada25da19784 |
completed | May 22, 2026, 2:37 p.m. |
Created at: April 21, 2026, 1:11 p.m.