Triple

T31269269
Position Surface form Disambiguated ID Type / Status
Subject Numbers 22–24 E797337 entity
Predicate chapterRange P21760 FINISHED
Object Numbers 23
Numbers 23 is a chapter in the Hebrew Bible/Old Testament that records part of the prophet Balaam’s oracles, in which he blesses Israel despite being summoned to curse them.
E1953360 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: Numbers 23 | Statement: [Numbers 22–24, chapterRange, Numbers 23]
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: Numbers 23
Triple: [Numbers 22–24, chapterRange, Numbers 23]
Generated description
Numbers 23 is a chapter in the Hebrew Bible/Old Testament that records part of the prophet Balaam’s oracles, in which he blesses Israel despite being summoned to curse them.

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_69f224de2bbc819081af6c32e1d857b9 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69dcb1d088190bf7c399aa7fc7331 completed May 3, 2026, 12:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a296c02d8d881909b060c517a83e0c1 completed June 10, 2026, 1:52 p.m.
NEDg Description generation batch_6a296d07c1488190a6e252822f8524fd completed June 10, 2026, 1:56 p.m.
NED2 Entity disambiguation (via description) batch_6a299d6014388190973ba4c5f6fadbb3 completed June 10, 2026, 5:22 p.m.
Created at: April 29, 2026, 9:13 p.m.