Triple

T27984516
Position Surface form Disambiguated ID Type / Status
Subject South Philadelphia street network E706707 entity
Predicate hasMajorStreet P30026 FINISHED
Object Moyamensing Avenue
Moyamensing Avenue is a major north–south thoroughfare running through South Philadelphia, known for connecting residential neighborhoods with commercial and industrial areas.
E2293491 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: Moyamensing Avenue | Statement: [South Philadelphia street network, hasMajorStreet, Moyamensing 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: Moyamensing Avenue
Triple: [South Philadelphia street network, hasMajorStreet, Moyamensing Avenue]
Generated description
Moyamensing Avenue is a major north–south thoroughfare running through South Philadelphia, known for connecting residential neighborhoods with commercial and industrial areas.

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_69ef96b8b8d88190bad5e4ae966bf14e completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69f63b6bf1d881908818670a5daa816e completed May 2, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7ab319ec04819095ea5ba31cf955d1 completed Aug. 11, 2026, 5:28 a.m.
NEDg Description generation batch_6a7ab43ed7b48190bb27710f67774a9c completed Aug. 11, 2026, 5:33 a.m.
NED2 Entity disambiguation (via description) batch_6a7ab49eeda48190822a8af11cd77a9e completed Aug. 11, 2026, 5:35 a.m.
Created at: April 27, 2026, 7:46 p.m.