Triple

T32087021
Position Surface form Disambiguated ID Type / Status
Subject Ponterwyd E819474 entity
Predicate hasNearbyAttraction P2064 FINISHED
Object Cwm Rheidol Reservoir
Cwm Rheidol Reservoir is a scenic artificial lake in Ceredigion, Wales, known for its surrounding forested valley, hydroelectric power station, and opportunities for walking and wildlife watching.
E1992548 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: Cwm Rheidol Reservoir | Statement: [Ponterwyd, hasNearbyAttraction, Cwm Rheidol Reservoir]
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: Cwm Rheidol Reservoir
Triple: [Ponterwyd, hasNearbyAttraction, Cwm Rheidol Reservoir]
Generated description
Cwm Rheidol Reservoir is a scenic artificial lake in Ceredigion, Wales, known for its surrounding forested valley, hydroelectric power station, and opportunities for walking and wildlife watching.

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_69f349004b2481908ce2e50af0d579a8 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b58bbf34819093fd432a2b5e5bda completed May 3, 2026, 2:40 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2f011bcb788190b4748cc6d8f33716 completed June 14, 2026, 7:29 p.m.
NEDg Description generation batch_6a2f01ea7af48190b512828f4f61f118 completed June 14, 2026, 7:32 p.m.
NED2 Entity disambiguation (via description) batch_6a2f02b7f21c81908bbf45cf1a616aab completed June 14, 2026, 7:36 p.m.
Created at: May 1, 2026, 12:25 a.m.