Triple

T27553275
Position Surface form Disambiguated ID Type / Status
Subject Bridge City, Texas E695561 entity
Predicate transportCorridor P3034 FINISHED
Object Texas State Highway 73
Texas State Highway 73 is a major east–west state highway in southeast Texas that connects the Port Arthur/Beaumont area with communities near the Louisiana border.
E2030713 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 73 | Statement: [Bridge City, Texas, transportCorridor, Texas State Highway 73]
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 73
Triple: [Bridge City, Texas, transportCorridor, Texas State Highway 73]
Generated description
Texas State Highway 73 is a major east–west state highway in southeast Texas that connects the Port Arthur/Beaumont area with communities near the Louisiana border.

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_69ef5387e97c8190a9dab040d21cd048 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62f8e4ab88190bfe86343b948a401 completed May 2, 2026, 5:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a34d239177c8190b740a9c3804e4484 completed June 19, 2026, 5:23 a.m.
NEDg Description generation batch_6a34d3bdb6808190967b4c67d5a3af66 completed June 19, 2026, 5:29 a.m.
NED2 Entity disambiguation (via description) batch_6a34d46b4a4081909c03beb97142b28e completed June 19, 2026, 5:32 a.m.
Created at: April 27, 2026, 1:35 p.m.