Triple

T35990210
Position Surface form Disambiguated ID Type / Status
Subject John Boyle O'Reilly E1040822 entity
Predicate employer P7 FINISHED
Object The Pilot (Boston newspaper)
The Pilot was a prominent 19th-century Boston-based Catholic newspaper known for serving the Irish-American community and engaging in political and social issues of its time.
E2165815 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: The Pilot (Boston newspaper) | Statement: [John Boyle O'Reilly, employer, The Pilot (Boston newspaper)]
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: The Pilot (Boston newspaper)
Triple: [John Boyle O'Reilly, employer, The Pilot (Boston newspaper)]
Generated description
The Pilot was a prominent 19th-century Boston-based Catholic newspaper known for serving the Irish-American community and engaging in political and social issues of its time.

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_69f76e29084c819083987b828d414de7 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7ac5a1d4c8190882a4977986d3712 completed May 3, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38bfe9f4448190b271097193ead28a completed June 22, 2026, 4:54 a.m.
NEDg Description generation batch_6a38c3bffd888190b9cb3baed991ea3a completed June 22, 2026, 5:10 a.m.
NED2 Entity disambiguation (via description) batch_6a38c437221c81909bbe2678714092f8 completed June 22, 2026, 5:12 a.m.
Created at: May 3, 2026, 4:07 p.m.