Triple

T25661520
Position Surface form Disambiguated ID Type / Status
Subject Médéa Province E643396 entity
Predicate borderingProvince P224 FINISHED
Object Aïn Defla Province
Aïn Defla Province is an administrative region in northern Algeria known for its agricultural plains and strategic location along major transport routes west of Algiers.
E1983696 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: Aïn Defla Province | Statement: [Médéa Province, borderingProvince, Aïn Defla Province]
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: Aïn Defla Province
Triple: [Médéa Province, borderingProvince, Aïn Defla Province]
Generated description
Aïn Defla Province is an administrative region in northern Algeria known for its agricultural plains and strategic location along major transport routes west of Algiers.

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_69e77e7e45648190a068ed3faa8016ea completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5faef72a88190b6401a319638ff14 completed May 2, 2026, 1:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2e8a08b790819098ebe9286e5ab111 completed June 14, 2026, 11:01 a.m.
NEDg Description generation batch_6a2e8ad753688190829398ff32cf09e8 completed June 14, 2026, 11:04 a.m.
NED2 Entity disambiguation (via description) batch_6a2e8b9c48a48190a1c5bef0fe49f633 completed June 14, 2026, 11:08 a.m.
Created at: April 21, 2026, 6:54 p.m.