Triple

T34750897
Position Surface form Disambiguated ID Type / Status
Subject Inwood Road E1001773 entity
Predicate hasJunctionWith P1018 FINISHED
Object Lemmon Avenue
Lemmon Avenue is a major thoroughfare in Dallas, Texas, known for connecting several central neighborhoods and commercial areas, including its junction with Inwood Road.
E2296833 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: Lemmon Avenue | Statement: [Inwood Road, hasJunctionWith, Lemmon 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: Lemmon Avenue
Triple: [Inwood Road, hasJunctionWith, Lemmon Avenue]
Generated description
Lemmon Avenue is a major thoroughfare in Dallas, Texas, known for connecting several central neighborhoods and commercial areas, including its junction with Inwood Road.

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_69f76db0367081909b57c50a7fb03025 completed May 3, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f779eab83481909e041bdfbebff34c completed May 3, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a82c183c08c8190b638197463e58444 completed Aug. 17, 2026, 8:08 a.m.
NEDg Description generation batch_6a82c2fae1ec8190ad4d34a3c9aed609 completed Aug. 17, 2026, 8:14 a.m.
NED2 Entity disambiguation (via description) batch_6a82c354fa4481908adcdcf3732a7c65 completed Aug. 17, 2026, 8:16 a.m.
Created at: May 3, 2026, 3:59 p.m.