Triple

T36710748
Position Surface form Disambiguated ID Type / Status
Subject Leviticus 27:33 E906787 entity
Predicate follows P134 FINISHED
Object Leviticus 27:32
Leviticus 27:32 is a verse in the Old Testament that outlines laws concerning the tithing of livestock to the Lord.
E2198097 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: Leviticus 27:32 | Statement: [Leviticus 27:33, follows, Leviticus 27:32]
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: Leviticus 27:32
Triple: [Leviticus 27:33, follows, Leviticus 27:32]
Generated description
Leviticus 27:32 is a verse in the Old Testament that outlines laws concerning the tithing of livestock to the Lord.

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_69f76e73ad108190a5241585f2303e9a completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c812e2f481909d90451f25013476 completed May 3, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3c172439988190ae0c57a03f60c1ea completed June 24, 2026, 5:43 p.m.
NEDg Description generation batch_6a3c17bef5988190bf7bbafbaaeebef1 completed June 24, 2026, 5:45 p.m.
NED2 Entity disambiguation (via description) batch_6a3c6c139c748190befd6b09cf6171b2 completed June 24, 2026, 11:45 p.m.
Created at: May 3, 2026, 4:12 p.m.