Triple

T15820907
Position Surface form Disambiguated ID Type / Status
Subject Clydach, Glamorganshire, Wales E383603 entity
Predicate hasTransport P1298 FINISHED
Object A4067 road
The A4067 road is a major route in South Wales that connects Swansea with the Brecon Beacons area, running through the Swansea Valley and serving communities such as Clydach.
E2151496 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: A4067 road | Statement: [Clydach, Glamorganshire, Wales, hasTransport, A4067 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: A4067 road
Triple: [Clydach, Glamorganshire, Wales, hasTransport, A4067 road]
Generated description
The A4067 road is a major route in South Wales that connects Swansea with the Brecon Beacons area, running through the Swansea Valley and serving communities such as Clydach.

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_69d86da2858c819090cc8481e7207b6e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0c4a7ba4881908a2747bf063d79f1 completed April 16, 2026, 11:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a38725e23a48190b4ae4b6f8f9c8db2 completed June 21, 2026, 11:23 p.m.
NEDg Description generation batch_6a3872c94a648190b9e30db479a9481b completed June 21, 2026, 11:24 p.m.
NED2 Entity disambiguation (via description) batch_6a387337fa9c8190833f60c3a5bbb20a completed June 21, 2026, 11:26 p.m.
Created at: April 10, 2026, 4:49 a.m.