Triple

T34072480
Position Surface form Disambiguated ID Type / Status
Subject Tamanrasset Province E873809 entity
Predicate transportInfrastructure P1777 FINISHED
Object Tamanrasset Airport
Tamanrasset Airport is a public airport in southern Algeria that serves the city of Tamanrasset and acts as a key aviation hub for the surrounding Saharan region.
E2089842 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: Tamanrasset Airport | Statement: [Tamanrasset Province, transportInfrastructure, Tamanrasset Airport]
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: Tamanrasset Airport
Triple: [Tamanrasset Province, transportInfrastructure, Tamanrasset Airport]
Generated description
Tamanrasset Airport is a public airport in southern Algeria that serves the city of Tamanrasset and acts as a key aviation hub for the surrounding Saharan region.

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_69f349a566808190a1c63b898f33cddf completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f70bd02e0c8190a1b88d3ff6e64ad2 completed May 3, 2026, 8:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36e60ae0b481908360dd0182f052b6 completed June 20, 2026, 7:12 p.m.
NEDg Description generation batch_6a36ea139e9081909f2f42897e005dfa completed June 20, 2026, 7:29 p.m.
NED2 Entity disambiguation (via description) batch_6a36ea6e1fc881909b7743c57c7635b8 completed June 20, 2026, 7:30 p.m.
Created at: May 1, 2026, 1:52 a.m.