Triple

T33151606
Position Surface form Disambiguated ID Type / Status
Subject Brian Lenihan Snr E848452 entity
Predicate spouse P13 FINISHED
Object Ann Lenihan
Ann Lenihan was the wife of prominent Irish politician Brian Lenihan Snr and a member of a well-known Irish political family.
E2077383 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: Ann Lenihan | Statement: [Brian Lenihan Snr, spouse, Ann Lenihan]
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: Ann Lenihan
Triple: [Brian Lenihan Snr, spouse, Ann Lenihan]
Generated description
Ann Lenihan was the wife of prominent Irish politician Brian Lenihan Snr and a member of a well-known Irish political family.

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_69f3495a458c8190a1d34b237ba0be3f completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d897e5448190956be2cd2746c14c completed May 3, 2026, 5:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a3692ba2a008190891fe7fbb5ca6644 completed June 20, 2026, 1:16 p.m.
NEDg Description generation batch_6a3693c6c72081908b00643cc42b85d1 completed June 20, 2026, 1:21 p.m.
NED2 Entity disambiguation (via description) batch_6a3694b83d048190a29c179e9407f41f completed June 20, 2026, 1:25 p.m.
Created at: May 1, 2026, 1:28 a.m.