Triple

T33395052
Position Surface form Disambiguated ID Type / Status
Subject Mighty Hood E855148 entity
Predicate memorializedBy P500 FINISHED
Object HMS Hood Association
The HMS Hood Association is an organization dedicated to preserving the history and memory of the British battlecruiser HMS Hood and those who served on her.
E2049977 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: HMS Hood Association | Statement: [Mighty Hood, memorializedBy, HMS Hood Association]
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: HMS Hood Association
Triple: [Mighty Hood, memorializedBy, HMS Hood Association]
Generated description
The HMS Hood Association is an organization dedicated to preserving the history and memory of the British battlecruiser HMS Hood and those who served on her.

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_69f3496e3f1c8190bcecfa82aa9d17ff completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f6e40c55dc81909cff4f6362dda5b1 completed May 3, 2026, 5:58 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3576f1b91881908ff563d9c69e150b completed June 19, 2026, 5:05 p.m.
NEDg Description generation batch_6a3579d851108190a0abbaac8db8b9c6 completed June 19, 2026, 5:18 p.m.
NED2 Entity disambiguation (via description) batch_6a357a37b08481908bd9fd5c1eb65cb9 completed June 19, 2026, 5:19 p.m.
Created at: May 1, 2026, 1:35 a.m.