Triple

T30296930
Position Surface form Disambiguated ID Type / Status
Subject El Obeid E770543 entity
Predicate roadConnection P385 FINISHED
Object Khartoum–El Obeid highway
The Khartoum–El Obeid highway is a major road in Sudan that links the capital, Khartoum, with the regional center of El Obeid, facilitating transport and trade across central Sudan.
E1908537 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: Khartoum–El Obeid highway | Statement: [El Obeid, roadConnection, Khartoum–El Obeid highway]
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: Khartoum–El Obeid highway
Triple: [El Obeid, roadConnection, Khartoum–El Obeid highway]
Generated description
The Khartoum–El Obeid highway is a major road in Sudan that links the capital, Khartoum, with the regional center of El Obeid, facilitating transport and trade across central Sudan.

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_69f224881b948190b8c4921b250a44a3 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f68137aa048190937c6a9397ea514e completed May 2, 2026, 10:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276f0a8d2c8190bc3009d8f50e529d completed June 9, 2026, 1:40 a.m.
NEDg Description generation batch_6a27702ecf848190b13834994670c6a2 completed June 9, 2026, 1:45 a.m.
NED2 Entity disambiguation (via description) batch_6a2770a076148190884c0e1e91c27114 completed June 9, 2026, 1:47 a.m.
Created at: April 29, 2026, 7:48 p.m.