Triple

T23944623
Position Surface form Disambiguated ID Type / Status
Subject Post-it Notes E602880 entity
Predicate hasVariant P455 FINISHED
Object Post-it Easel Pads
Post-it Easel Pads are large, portable self-stick flip-chart pads designed for capturing and displaying group ideas during meetings, presentations, and brainstorming sessions.
 E602880 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: Post-it Easel Pads | Statement: [Post-it Notes, hasVariant, Post-it Easel Pads]
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: Post-it Easel Pads
Triple: [Post-it Notes, hasVariant, Post-it Easel Pads]
Generated description
Post-it Easel Pads are large, portable self-stick flip-chart pads designed for capturing and displaying group ideas during meetings, presentations, and brainstorming sessions.

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_69e2953e4924819093f1c24c03476b42 completed April 17, 2026, 8:17 p.m.
NER Named-entity recognition batch_69f1d02d07b08190acbcbb646cd9a58e completed April 29, 2026, 9:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f76518be8819089e44adbc027e516 completed May 21, 2026, 9:17 p.m.
NEDg Description generation batch_6a0f77225bec81908590adc4f49a1e1e completed May 21, 2026, 9:20 p.m.
NED2 Entity disambiguation (via description) batch_6a0f78c456dc8190869c04d4a5c00ceb completed May 21, 2026, 9:27 p.m.
Created at: April 17, 2026, 9:11 p.m.