Triple

T36843247
Position Surface form Disambiguated ID Type / Status
Subject Weches, Texas E910465 entity
Predicate transportationAccess P941 FINISHED
Object Farm to Market Road 227
Farm to Market Road 227 is a Texas state-maintained rural roadway that connects small communities and agricultural areas in the region around Weches.
E2202810 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 227 | Statement: [Weches, Texas, transportationAccess, Farm to Market Road 227]
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 227
Triple: [Weches, Texas, transportationAccess, Farm to Market Road 227]
Generated description
Farm to Market Road 227 is a Texas state-maintained rural roadway that connects small communities and agricultural areas in the region around Weches.

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_69f76e7f65a881908651b702da592b6d completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7cfa58bb481908bcf747c84529987 completed May 3, 2026, 10:43 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3dfad8105c8190acdd94fed2db7e89 completed June 26, 2026, 4:06 a.m.
NEDg Description generation batch_6a3dfdd8e75881909ed9b1e92c29e521 completed June 26, 2026, 4:19 a.m.
NED2 Entity disambiguation (via description) batch_6a3e04c40940819093a2f5b932aadea8 completed June 26, 2026, 4:49 a.m.
Created at: May 3, 2026, 4:13 p.m.