Triple

T29035446
Position Surface form Disambiguated ID Type / Status
Subject Lisp Machines, Inc. E737845 entity
Predicate competitor P1375 FINISHED
Object Texas Instruments Lisp machines
Texas Instruments Lisp machines were specialized workstations developed by Texas Instruments in the 1980s to efficiently run the Lisp programming language for artificial intelligence and symbolic computing applications.
E1485430 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: Texas Instruments Lisp machines | Statement: [Lisp Machines, Inc., competitor, Texas Instruments Lisp machines]
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: Texas Instruments Lisp machines
Triple: [Lisp Machines, Inc., competitor, Texas Instruments Lisp machines]
Generated description
Texas Instruments Lisp machines were specialized workstations developed by Texas Instruments in the 1980s to efficiently run the Lisp programming language for artificial intelligence and symbolic computing applications.

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_69f077efb3848190b41574e1670f6ae2 completed April 28, 2026, 9:03 a.m.
NER Named-entity recognition batch_69f6603c9e4081908129011e8294db5a completed May 2, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2505d9c09c81908bf3d87590cbdc3d completed June 7, 2026, 5:47 a.m.
NEDg Description generation batch_6a250af483c08190b831fed9367c84c0 completed June 7, 2026, 6:08 a.m.
NED2 Entity disambiguation (via description) batch_6a250f52bc788190a19327674f832883 completed June 7, 2026, 6:27 a.m.
Created at: April 28, 2026, 9:58 a.m.