Triple

T27225348
Position Surface form Disambiguated ID Type / Status
Subject Farm to Market Road 455 E681394 entity
Predicate hasJunctionWith P1018 FINISHED
Object Farm to Market Road 2450
Farm to Market Road 2450 is a Texas state-maintained secondary roadway serving rural and agricultural areas and connecting local communities to larger highway routes.
E1762490 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: Farm to Market Road 2450 | Statement: [Farm to Market Road 455, hasJunctionWith, Farm to Market Road 2450]
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: Farm to Market Road 2450
Triple: [Farm to Market Road 455, hasJunctionWith, Farm to Market Road 2450]
Generated description
Farm to Market Road 2450 is a Texas state-maintained secondary roadway serving rural and agricultural areas and connecting local communities to larger highway routes.

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_69eefac9f64c8190a07490fe0c8b72a3 completed April 27, 2026, 5:57 a.m.
NER Named-entity recognition batch_69f6264a03648190a9b6904ce2f7aeeb completed May 2, 2026, 4:28 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12626e884c819092986b7623d9ac27 completed May 24, 2026, 2:29 a.m.
NEDg Description generation batch_6a1263a80d848190ac06c46e255e9b26 completed May 24, 2026, 2:34 a.m.
NED2 Entity disambiguation (via description) batch_6a126448a36c8190837c7ea378f68cd3 completed May 24, 2026, 2:36 a.m.
Created at: April 27, 2026, 9:44 a.m.