Triple

T20447318
Position Surface form Disambiguated ID Type / Status
Subject Aughnacloy E501550 entity
Predicate locatedOn P40 FINISHED
Object A4 road
The A4 road is a major route in Northern Ireland that connects Belfast to the western regions, including towns such as Aughnacloy and Enniskillen.
E1662245 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: A4 road | Statement: [Aughnacloy, locatedOn, A4 road]
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: A4 road
Triple: [Aughnacloy, locatedOn, A4 road]
Generated description
The A4 road is a major route in Northern Ireland that connects Belfast to the western regions, including towns such as Aughnacloy and Enniskillen.

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_69e0b4ac0a1c81908845d0f8a56abce8 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e68cfe57a8819094bd3d324bd567f5 completed April 20, 2026, 8:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10485ba70c819092ab75db8a67dceb completed May 22, 2026, 12:13 p.m.
NEDg Description generation batch_6a104a2a89e08190aa35e97ffb57fc9a completed May 22, 2026, 12:20 p.m.
NED2 Entity disambiguation (via description) batch_6a104bc667e48190bb0feadc5b324cde completed May 22, 2026, 12:27 p.m.
Created at: April 16, 2026, 11:32 a.m.