Triple

T22207879
Position Surface form Disambiguated ID Type / Status
Subject Gilmer, Texas E548862 entity
Predicate roadAccess P385 FINISHED
Object Texas State Highway 300
Texas State Highway 300 is a state-maintained roadway in northeast Texas that connects the city of Longview with the town of Gilmer, serving as a regional commuter and freight route.
E1697404 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: Texas State Highway 300 | Statement: [Gilmer, Texas, roadAccess, Texas State Highway 300]
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: Texas State Highway 300
Triple: [Gilmer, Texas, roadAccess, Texas State Highway 300]
Generated description
Texas State Highway 300 is a state-maintained roadway in northeast Texas that connects the city of Longview with the town of Gilmer, serving as a regional commuter and freight route.

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_69e11e3f7e04819089806d81d5ac431e completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f12b2936a481909aa84c7983ed49ee completed April 28, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10d9cc70808190b72a2d2bf7d14568 completed May 22, 2026, 10:33 p.m.
NEDg Description generation batch_6a10ddc8e4188190959ea1e7d360aba5 completed May 22, 2026, 10:50 p.m.
NED2 Entity disambiguation (via description) batch_6a10de259fd4819087f0f5707196792d completed May 22, 2026, 10:52 p.m.
Created at: April 16, 2026, 8:36 p.m.