Triple

T25872555
Position Surface form Disambiguated ID Type / Status
Subject Alameda County Fairgrounds E651797 entity
Predicate hosts P186 FINISHED
Object Alameda County Fair
The Alameda County Fair is an annual summer fair in Pleasanton, California, featuring carnival rides, live entertainment, livestock shows, horse racing, and a wide variety of food and community events.
E1697695 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: Alameda County Fair | Statement: [Alameda County Fairgrounds, hosts, Alameda County Fair]
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: Alameda County Fair
Triple: [Alameda County Fairgrounds, hosts, Alameda County Fair]
Generated description
The Alameda County Fair is an annual summer fair in Pleasanton, California, featuring carnival rides, live entertainment, livestock shows, horse racing, and a wide variety of food and community events.

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_69e7ab3ad9d88190841ddcb93ab02e96 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f602dd86dc8190b36335017d158398 completed May 2, 2026, 1:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10da4813fc81908b91387833c33381 completed May 22, 2026, 10:35 p.m.
NEDg Description generation batch_6a10de66d72881909bb8d8197f717865 completed May 22, 2026, 10:53 p.m.
NED2 Entity disambiguation (via description) batch_6a10df0972a0819084978d229eaddd67 completed May 22, 2026, 10:56 p.m.
Created at: April 22, 2026, 8:11 a.m.