Triple

T26477950
Position Surface form Disambiguated ID Type / Status
Subject John Battelle E666091 entity
Predicate coFounded P104 FINISHED
Object Industry Standard magazine
Industry Standard magazine was a prominent late-1990s technology and business publication that chronicled and analyzed the rise of the internet economy.
 E1726359 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: Industry Standard magazine | Statement: [John Battelle, coFounded, Industry Standard magazine]
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: Industry Standard magazine
Triple: [John Battelle, coFounded, Industry Standard magazine]
Generated description
Industry Standard magazine was a prominent late-1990s technology and business publication that chronicled and analyzed the rise of the internet economy.

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_69ee883f80dc819090e311b022b78e02 completed April 26, 2026, 9:48 p.m.
NER Named-entity recognition batch_69f612ce613081908f37874b9ecfe7cc completed May 2, 2026, 3:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11aee9256c8190b212248288fe0d90 completed May 23, 2026, 1:43 p.m.
NEDg Description generation batch_6a11af68d97c81908ccb1af29de6b417 completed May 23, 2026, 1:45 p.m.
NED2 Entity disambiguation (via description) batch_6a11b02a01f4819088f0f84f9ca335af completed May 23, 2026, 1:48 p.m.
Created at: April 27, 2026, 12:25 a.m.