Triple

T30288193
Position Surface form Disambiguated ID Type / Status
Subject What Richard Did E770295 entity
Predicate castMember P1668 FINISHED
Object Liana O’Cleirigh
Liana O’Cleirigh is an actress known for her role in the Irish drama film "What Richard Did."
E1945097 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: Liana O’Cleirigh | Statement: [What Richard Did, castMember, Liana O’Cleirigh]
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: Liana O’Cleirigh
Triple: [What Richard Did, castMember, Liana O’Cleirigh]
Generated description
Liana O’Cleirigh is an actress known for her role in the Irish drama film "What Richard Did."

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_69f224875c288190a9b96b975006ec4a completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6810a54a48190bc4af8a8a3ee261a completed May 2, 2026, 10:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a292aed33588190a97f5538bca52a6a completed June 10, 2026, 9:14 a.m.
NEDg Description generation batch_6a292bef9bb88190970e5b8830feda22 completed June 10, 2026, 9:18 a.m.
NED2 Entity disambiguation (via description) batch_6a292c909f1881908aa4f58707ae16da completed June 10, 2026, 9:21 a.m.
Created at: April 29, 2026, 7:46 p.m.