Triple

T24899824
Position Surface form Disambiguated ID Type / Status
Subject U.S. Highway 175 E623540 entity
Predicate hasJunctionWith P1018 FINISHED
Object Texas State Highway 243
Texas State Highway 243 is a state highway in Texas that runs east–west through Kaufman and Van Zandt counties, connecting several small communities and intersecting major routes in the region.
E1845303 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 243 | Statement: [U.S. Highway 175, hasJunctionWith, Texas State Highway 243]
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 243
Triple: [U.S. Highway 175, hasJunctionWith, Texas State Highway 243]
Generated description
Texas State Highway 243 is a state highway in Texas that runs east–west through Kaufman and Van Zandt counties, connecting several small communities and intersecting major routes in the region.

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_69e2fac797cc8190b30d77f4121099ac completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f42364b780819089299ef7ed95ec32 completed May 1, 2026, 3:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a25057ab76881908f770a3f2f559b4e completed June 7, 2026, 5:45 a.m.
NEDg Description generation batch_6a2509a2a3b08190b3fde8083c80eef6 completed June 7, 2026, 6:03 a.m.
NED2 Entity disambiguation (via description) batch_6a250e036044819085e601b07f88a7ff completed June 7, 2026, 6:21 a.m.
Created at: April 18, 2026, 5:27 a.m.