Triple

T31913474
Position Surface form Disambiguated ID Type / Status
Subject Utterly Monkey E814755 entity
Predicate writtenBy P806 FINISHED
Object Northern Irish writer Nick Laird
Northern Irish writer Nick Laird is a poet, novelist, and essayist known for his sharp, witty explorations of contemporary life, identity, and politics.
 E1981924 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: Northern Irish writer Nick Laird | Statement: [Utterly Monkey, writtenBy, Northern Irish writer Nick Laird]
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: Northern Irish writer Nick Laird
Triple: [Utterly Monkey, writtenBy, Northern Irish writer Nick Laird]
Generated description
Northern Irish writer Nick Laird is a poet, novelist, and essayist known for his sharp, witty explorations of contemporary life, identity, and politics.

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_69f348f109d88190b5005372c53d2fcd completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b1bb923881909dd346a3739c91c8 completed May 3, 2026, 2:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2e7ffb5d088190a9d0c555ff1b67a7 completed June 14, 2026, 10:18 a.m.
NEDg Description generation batch_6a2e808c5b1081909fdf8a3c7ab91459 completed June 14, 2026, 10:21 a.m.
NED2 Entity disambiguation (via description) batch_6a2e8155e4788190badcebd73ae27e02 completed June 14, 2026, 10:24 a.m.
Created at: May 1, 2026, 12:01 a.m.