Triple

T31125151
Position Surface form Disambiguated ID Type / Status
Subject The Animals E793334 entity
Predicate associatedWithMovement P2459 FINISHED
Object New York street photography
New York street photography is a genre of candid, urban photography that captures everyday life, characters, and moments on the streets of New York City, often emphasizing its energy, diversity, and distinctive visual atmosphere.
 E1947367 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: New York street photography | Statement: [The Animals, associatedWithMovement, New York street photography]
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: New York street photography
Triple: [The Animals, associatedWithMovement, New York street photography]
Generated description
New York street photography is a genre of candid, urban photography that captures everyday life, characters, and moments on the streets of New York City, often emphasizing its energy, diversity, and distinctive visual atmosphere.

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_69f224d1701c819094f429798290e361 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f6973b3b0c8190844b465a937a3b38 completed May 3, 2026, 12:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2938c32a6c8190b8a160152f04739c completed June 10, 2026, 10:13 a.m.
NEDg Description generation batch_6a293a06fef08190b9e8b9d10dba3cef completed June 10, 2026, 10:18 a.m.
NED2 Entity disambiguation (via description) batch_6a293a9c8cdc8190aceb7ddf2ae5e038 completed June 10, 2026, 10:21 a.m.
Created at: April 29, 2026, 9:05 p.m.