Triple

T32590259
Position Surface form Disambiguated ID Type / Status
Subject Seymour Narrows E833042 entity
Predicate namedAfter P63 FINISHED
Object Admiral Sir George Francis Seymour
Admiral Sir George Francis Seymour was a 19th-century British Royal Navy officer who rose to high command and served in several important naval and colonial posts.
 E2014374 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: Admiral Sir George Francis Seymour | Statement: [Seymour Narrows, namedAfter, Admiral Sir George Francis Seymour]
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: Admiral Sir George Francis Seymour
Triple: [Seymour Narrows, namedAfter, Admiral Sir George Francis Seymour]
Generated description
Admiral Sir George Francis Seymour was a 19th-century British Royal Navy officer who rose to high command and served in several important naval and colonial posts.

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_69f34929ff648190aded9424aa7564ae completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c67138e8819099aa4ded014143ba completed May 3, 2026, 3:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a34860b69a08190ae65e542eba00d89 completed June 18, 2026, 11:58 p.m.
NEDg Description generation batch_6a3486a95ecc8190b58597914c9a809c completed June 19, 2026, midnight
NED2 Entity disambiguation (via description) batch_6a348767eeb08190b80bf696b49d1f21 completed June 19, 2026, 12:03 a.m.
Created at: May 1, 2026, 1:05 a.m.