Triple

T35028725
Position Surface form Disambiguated ID Type / Status
Subject Linden, Guyana E1010415 entity
Predicate transportLink P11026 FINISHED
Object Linden–Soesdyke Highway
The Linden–Soesdyke Highway is a major roadway in Guyana that connects the inland town of Linden with the coastal area near Georgetown, facilitating regional transport and access to the interior.
 E2160851 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: Linden–Soesdyke Highway | Statement: [Linden, Guyana, transportLink, Linden–Soesdyke 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: Linden–Soesdyke Highway
Triple: [Linden, Guyana, transportLink, Linden–Soesdyke Highway]
Generated description
The Linden–Soesdyke Highway is a major roadway in Guyana that connects the inland town of Linden with the coastal area near Georgetown, facilitating regional transport and access to the interior.

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_69f76dccf0108190af43b465d3750196 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7854569208190a5c3bd8e5f8a8ea3 completed May 3, 2026, 5:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38ae0b04dc8190a378db1c6183e583 completed June 22, 2026, 3:37 a.m.
NEDg Description generation batch_6a38ae71ff8c8190a30842929e377636 completed June 22, 2026, 3:39 a.m.
NED2 Entity disambiguation (via description) batch_6a38af2d534881909253139da5a5e7da completed June 22, 2026, 3:42 a.m.
Created at: May 3, 2026, 4:01 p.m.