Triple

T30710042
Position Surface form Disambiguated ID Type / Status
Subject Monmouth's march towards Bristol E781865 entity
Predicate hasLocation P40 FINISHED
Object Bristol
Bristol is a historic port city in southwest England known for its maritime heritage, cultural scene, and role in various significant events in British history.
E16444 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: Bristol | Statement: [Monmouth's march towards Bristol, hasLocation, Bristol]
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: Bristol
Triple: [Monmouth's march towards Bristol, hasLocation, Bristol]
Generated description
Bristol is a historic port city in southwest England known for its maritime heritage, cultural scene, and role in various significant events in British history.

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_69f224abfcf081909492e64d3cc35262 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68c1e3fa48190bb3dd7c511dc3a56 completed May 2, 2026, 11:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28bbca45888190b684d3f2cdf1ba5b completed June 10, 2026, 1:20 a.m.
NEDg Description generation batch_6a28bde273288190a81a02ea796ca603 completed June 10, 2026, 1:29 a.m.
NED2 Entity disambiguation (via description) batch_6a28bed6aa2c819099259e4b892b8af3 completed June 10, 2026, 1:33 a.m.
Created at: April 29, 2026, 8:35 p.m.