Triple

T24829367
Position Surface form Disambiguated ID Type / Status
Subject Walnut Lane Memorial Bridge E621290 entity
Predicate carries P1393 FINISHED
Object Walnut Lane
Walnut Lane is a roadway in Philadelphia, Pennsylvania, that runs through the Wissahickon Valley and is notable for being spanned by the historic Walnut Lane Memorial Bridge.
E1682756 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: Walnut Lane | Statement: [Walnut Lane Memorial Bridge, carries, Walnut Lane]
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: Walnut Lane
Triple: [Walnut Lane Memorial Bridge, carries, Walnut Lane]
Generated description
Walnut Lane is a roadway in Philadelphia, Pennsylvania, that runs through the Wissahickon Valley and is notable for being spanned by the historic Walnut Lane Memorial Bridge.

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_69e2fac0c3b881909110e5a56c6fa46f completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f422b06aec81908885429764059103 completed May 1, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10ad2beb508190b25d86d8cf35dfbc completed May 22, 2026, 7:23 p.m.
NEDg Description generation batch_6a10ae2f577481909be995d38010dcf7 completed May 22, 2026, 7:27 p.m.
NED2 Entity disambiguation (via description) batch_6a10aef10de8819099e12e65f4f9e768 completed May 22, 2026, 7:30 p.m.
Created at: April 18, 2026, 5:12 a.m.