Triple

T27992696
Position Surface form Disambiguated ID Type / Status
Subject Drake Well E706922 entity
Predicate associatedWithPerson P37 FINISHED
Object James M. Townsend
James M. Townsend was a 19th-century figure connected to the early American oil industry through his association with the historic Drake Well in Pennsylvania.
E2297487 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 M. Townsend | Statement: [Drake Well, associatedWithPerson, James M. Townsend]
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 M. Townsend
Triple: [Drake Well, associatedWithPerson, James M. Townsend]
Generated description
James M. Townsend was a 19th-century figure connected to the early American oil industry through his association with the historic Drake Well in Pennsylvania.

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_69ef96b980d88190a753b2f9a978595a completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f63ba8ff308190876c52b659e5979d completed May 2, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_6a838adfb0f88190a584fc349d1951f2 completed Aug. 17, 2026, 10:27 p.m.
NEDg Description generation batch_6a838b4011788190a9d7f8316455deaf completed Aug. 17, 2026, 10:29 p.m.
NED2 Entity disambiguation (via description) batch_6a838b5c747c8190a99e26147be6ebae completed Aug. 17, 2026, 10:29 p.m.
Created at: April 27, 2026, 7:51 p.m.