Triple

T24631647
Position Surface form Disambiguated ID Type / Status
Subject Royal College of Psychiatrists E609690 entity
Predicate publishes P80 FINISHED
Object BJPsych Bulletin
BJPsych Bulletin is a peer-reviewed psychiatric journal that publishes research, reviews, and commentary on mental health practice, policy, and education.
E1648490 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: BJPsych Bulletin | Statement: [Royal College of Psychiatrists, publishes, BJPsych Bulletin]
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: BJPsych Bulletin
Triple: [Royal College of Psychiatrists, publishes, BJPsych Bulletin]
Generated description
BJPsych Bulletin is a peer-reviewed psychiatric journal that publishes research, reviews, and commentary on mental health practice, policy, and education.

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_69e2c4d1d3708190a0f2dc6a3a8523bb completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f2aabb5e6481909b209d4f38cb58b9 completed April 30, 2026, 1:04 a.m.
NED1 Entity disambiguation (via context triple) batch_6a100fef08a88190b88f5f3e67ff273c completed May 22, 2026, 8:12 a.m.
NEDg Description generation batch_6a10136992b481909ee04d5c09867f21 completed May 22, 2026, 8:27 a.m.
NED2 Entity disambiguation (via description) batch_6a10140b2fec8190aa6d805f54926b56 completed May 22, 2026, 8:30 a.m.
Created at: April 18, 2026, 2:32 a.m.