Triple

T27469744
Position Surface form Disambiguated ID Type / Status
Subject Tracy B. Strong E693280 entity
Predicate notableWork P4 FINISHED
Object Politics Without Vision
Politics Without Vision is a political theory book by Tracy B. Strong that critically examines the foundations and trajectory of modern Western political thought.
 E1774199 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: Politics Without Vision | Statement: [Tracy B. Strong, notableWork, Politics Without Vision]
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: Politics Without Vision
Triple: [Tracy B. Strong, notableWork, Politics Without Vision]
Generated description
Politics Without Vision is a political theory book by Tracy B. Strong that critically examines the foundations and trajectory of modern Western political thought.

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_69ef538105548190a771cc5a0cf8c211 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62e00d1148190bb61a0e1c090a3ff completed May 2, 2026, 5:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12bbe0d6a881909af7363d313dc2c5 completed May 24, 2026, 8:50 a.m.
NEDg Description generation batch_6a12bc482bb481908d121283f113dbb8 completed May 24, 2026, 8:52 a.m.
NED2 Entity disambiguation (via description) batch_6a12bcd0c164819098f637afcad01642 completed May 24, 2026, 8:54 a.m.
Created at: April 27, 2026, 12:53 p.m.