Triple

T34921389
Position Surface form Disambiguated ID Type / Status
Subject Greenwood Cemetery, New Orleans, Louisiana, United States E1007147 entity
Predicate locatedOn P40 FINISHED
Object City Park Avenue
City Park Avenue is a major thoroughfare in New Orleans, Louisiana, that runs along the edge of City Park and several historic cemeteries.
E2296952 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: City Park Avenue | Statement: [Greenwood Cemetery, New Orleans, Louisiana, United States, locatedOn, City Park Avenue]
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: City Park Avenue
Triple: [Greenwood Cemetery, New Orleans, Louisiana, United States, locatedOn, City Park Avenue]
Generated description
City Park Avenue is a major thoroughfare in New Orleans, Louisiana, that runs along the edge of City Park and several historic cemeteries.

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_69f76dc2b6b0819095a61debbd405269 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f782188ae48190a0d9a38d701ebc96 completed May 3, 2026, 5:12 p.m.
NED1 Entity disambiguation (via context triple) batch_6a82e255d2ac8190876d840aa1ae74f5 completed Aug. 17, 2026, 10:28 a.m.
NEDg Description generation batch_6a82e2b8e76081909f0e207fd2276bc7 completed Aug. 17, 2026, 10:30 a.m.
NED2 Entity disambiguation (via description) batch_6a82e5918d2c81909b386bdca6c8b3ec completed Aug. 17, 2026, 10:42 a.m.
Created at: May 3, 2026, 4 p.m.