Triple

T27670756
Position Surface form Disambiguated ID Type / Status
Subject Balch E697654 entity
Predicate hasNotableBearer P458 FINISHED
Object Francis V. Balch
Francis V. Balch was a 19th-century American lawyer and legal scholar known for his work in property and trust law.
 E1893383 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: Francis V. Balch | Statement: [Balch, hasNotableBearer, Francis V. Balch]
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: Francis V. Balch
Triple: [Balch, hasNotableBearer, Francis V. Balch]
Generated description
Francis V. Balch was a 19th-century American lawyer and legal scholar known for his work in property and trust law.

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_69ef590d458c81909583290c3cd0478b completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f634a8cf6481909e5cb8c9868bd90b completed May 2, 2026, 5:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2721c96fa481909ef1d8c941d94b04 completed June 8, 2026, 8:10 p.m.
NEDg Description generation batch_6a27226c29fc81909e79cb508975bc92 completed June 8, 2026, 8:13 p.m.
NED2 Entity disambiguation (via description) batch_6a27231dfdac8190870ab5105b8c174d completed June 8, 2026, 8:16 p.m.
Created at: April 27, 2026, 2:41 p.m.