Triple

T36446513
Position Surface form Disambiguated ID Type / Status
Subject Pearse Street E897887 entity
Predicate hasLandmark P105 FINISHED
Object Pearse House flats
Pearse House flats is a large early 20th-century public housing complex in Dublin, Ireland, known as one of the city’s most prominent examples of social housing architecture.
E2183994 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: Pearse House flats | Statement: [Pearse Street, hasLandmark, Pearse House flats]
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: Pearse House flats
Triple: [Pearse Street, hasLandmark, Pearse House flats]
Generated description
Pearse House flats is a large early 20th-century public housing complex in Dublin, Ireland, known as one of the city’s most prominent examples of social housing architecture.

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_69f76e5720b481908f8177ac24a7560b completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7bd8ca4a48190b2ea3ec1055a5a17 completed May 3, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39c41f1ea88190a9ed0877c513dbf9 completed June 22, 2026, 11:24 p.m.
NEDg Description generation batch_6a39c4c69e8c81909a8d39b83926666f completed June 22, 2026, 11:27 p.m.
NED2 Entity disambiguation (via description) batch_6a39c59ba6d48190a285f5b0f1adcdda completed June 22, 2026, 11:30 p.m.
Created at: May 3, 2026, 4:10 p.m.