Triple

T9687162
Position Surface form Disambiguated ID Type / Status
Subject Port Richmond E234439 entity
Predicate hasLandmark P105 FINISHED
Object Faber Park
Faber Park is a public waterfront park and recreational area in the Port Richmond neighborhood of Staten Island, New York City.
E2292174 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: Faber Park | Statement: [Port Richmond, hasLandmark, Faber Park]
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: Faber Park
Triple: [Port Richmond, hasLandmark, Faber Park]
Generated description
Faber Park is a public waterfront park and recreational area in the Port Richmond neighborhood of Staten Island, New York City.

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_69ca84ca73208190957a900c8543bdcc completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9cd42cc081909abcf4c85592d950 completed April 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a5ccd43a77c8190ad61abd803cba5b9 completed July 19, 2026, 1:12 p.m.
NEDg Description generation batch_6a5cce5a49188190a8b4a9167dc55eec completed July 19, 2026, 1:17 p.m.
NED2 Entity disambiguation (via description) batch_6a5ccec42abc8190a764c07c0544ebe2 completed July 19, 2026, 1:19 p.m.
Created at: March 30, 2026, 8:17 p.m.