Triple

T32459759
Position Surface form Disambiguated ID Type / Status
Subject George Sterling E829534 entity
Predicate birthPlace P1 FINISHED
Object Sagamore, New York
Sagamore, New York is a small community in the state of New York notable as the birthplace of poet and playwright George Sterling.
 E2016328 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: Sagamore, New York | Statement: [George Sterling, birthPlace, Sagamore, New York]
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: Sagamore, New York
Triple: [George Sterling, birthPlace, Sagamore, New York]
Generated description
Sagamore, New York is a small community in the state of New York notable as the birthplace of poet and playwright George Sterling.

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_69f3491df9288190afc0b23b1d6e72ce completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c31f10608190895cddc3444fae23 completed May 3, 2026, 3:38 a.m.
NED1 Entity disambiguation (via context triple) batch_6a349287cf4c81908612d0ab43ec1b7b completed June 19, 2026, 12:51 a.m.
NEDg Description generation batch_6a349371b8d88190a2c08921c9b35d27 completed June 19, 2026, 12:55 a.m.
NED2 Entity disambiguation (via description) batch_6a3493e636b08190852e2c7126ce950a completed June 19, 2026, 12:57 a.m.
Created at: May 1, 2026, 12:57 a.m.