Triple

T25907944
Position Surface form Disambiguated ID Type / Status
Subject Bechloul E652804 entity
Predicate locatedEastOf P4240 FINISHED
Object Algiers (by road, within northern Algeria)
Algiers (by road, within northern Algeria) is the capital and largest city of Algeria, situated on the Mediterranean coast in the country’s north.
E1702487 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: Algiers (by road, within northern Algeria) | Statement: [Bechloul, locatedEastOf, Algiers (by road, within northern Algeria)]
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: Algiers (by road, within northern Algeria)
Triple: [Bechloul, locatedEastOf, Algiers (by road, within northern Algeria)]
Generated description
Algiers (by road, within northern Algeria) is the capital and largest city of Algeria, situated on the Mediterranean coast in the country’s north.

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_69e7ab3d3f8481909bc53ed64c06af33 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f603c15b348190a7f00745b6475b28 completed May 2, 2026, 2:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecc9acb88190b00d90090301adbd completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10efdac5ac8190a3c71792453f5353 completed May 23, 2026, 12:07 a.m.
NED2 Entity disambiguation (via description) batch_6a10f05d3850819082219e205528bcbb completed May 23, 2026, 12:10 a.m.
Created at: April 22, 2026, 8:27 a.m.