Triple

T35881768
Position Surface form Disambiguated ID Type / Status
Subject A. D. Lindsay E1037527 entity
Predicate fullName P16 FINISHED
Object Alexander Dunlop Lindsay
Alexander Dunlop Lindsay was a British philosopher and academic who served as Master of Balliol College, Oxford, and was noted for his work on political philosophy and liberal education.
E2161430 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: Alexander Dunlop Lindsay | Statement: [A. D. Lindsay, fullName, Alexander Dunlop Lindsay]
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: Alexander Dunlop Lindsay
Triple: [A. D. Lindsay, fullName, Alexander Dunlop Lindsay]
Generated description
Alexander Dunlop Lindsay was a British philosopher and academic who served as Master of Balliol College, Oxford, and was noted for his work on political philosophy and liberal education.

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_69f76e1f4d748190bb55594d8441d70e completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7aa065f3081909d93382e7c8afbcf completed May 3, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ae214e1481908a4b367dcf0a0f11 completed June 22, 2026, 3:38 a.m.
NEDg Description generation batch_6a38af26a6088190956c385283dfcef6 completed June 22, 2026, 3:42 a.m.
NED2 Entity disambiguation (via description) batch_6a38afcce12c8190ba69d9dc33f5a8d7 completed June 22, 2026, 3:45 a.m.
Created at: May 3, 2026, 4:06 p.m.