Triple

T34841736
Position Surface form Disambiguated ID Type / Status
Subject Nevern E1004358 entity
Predicate hasArchaeologicalSiteNearby P14422 FINISHED
Object Nevern Castle
Nevern Castle is a medieval Norman stone and earthwork fortress in Pembrokeshire, Wales, known for its archaeological remains and historical significance in the Welsh–Norman conflicts.
E2120008 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: Nevern Castle | Statement: [Nevern, hasArchaeologicalSiteNearby, Nevern Castle]
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: Nevern Castle
Triple: [Nevern, hasArchaeologicalSiteNearby, Nevern Castle]
Generated description
Nevern Castle is a medieval Norman stone and earthwork fortress in Pembrokeshire, Wales, known for its archaeological remains and historical significance in the Welsh–Norman conflicts.

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_69f76db97714819099b5bed36fd64e9d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7813029f88190aa73c5bcae8611b3 completed May 3, 2026, 5:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37b2599c3c8190b7b9749e02184e7b completed June 21, 2026, 9:43 a.m.
NEDg Description generation batch_6a37b38d3bc4819094bf270b456b80b1 completed June 21, 2026, 9:49 a.m.
NED2 Entity disambiguation (via description) batch_6a37b47166f48190a351377c2080628e completed June 21, 2026, 9:52 a.m.
Created at: May 3, 2026, 4 p.m.