Triple

T34901133
Position Surface form Disambiguated ID Type / Status
Subject Richardson Dilworth E1006589 entity
Predicate succeededBy P78 FINISHED
Object James H. J. Tate
James H. J. Tate was an American politician who served as mayor of Philadelphia in the mid-20th century.
E2155330 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: James H. J. Tate | Statement: [Richardson Dilworth, succeededBy, James H. J. Tate]
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: James H. J. Tate
Triple: [Richardson Dilworth, succeededBy, James H. J. Tate]
Generated description
James H. J. Tate was an American politician who served as mayor of Philadelphia in the mid-20th century.

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_69f76dbfe5788190ad8b64f241f470c8 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f781e7a3d88190a49d97245f8734a3 completed May 3, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3885d2ecdc81909ae0f3af6d600799 completed June 22, 2026, 12:46 a.m.
NEDg Description generation batch_6a38875849188190a5f9af61de4904e0 completed June 22, 2026, 12:52 a.m.
NED2 Entity disambiguation (via description) batch_6a3888bbc4f481908007c1d0c99c9576 completed June 22, 2026, 12:58 a.m.
Created at: May 3, 2026, 4 p.m.