Triple

T30278403
Position Surface form Disambiguated ID Type / Status
Subject L’Auberge Casino Resort Lake Charles E770017 entity
Predicate locatedNear P294 FINISHED
Object Interstate 210
Interstate 210 is a bypass loop of Interstate 10 that serves the Lake Charles area in southwestern Louisiana, providing access to local destinations and easing through-traffic congestion.
E2293045 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: Interstate 210 | Statement: [L’Auberge Casino Resort Lake Charles, locatedNear, Interstate 210]
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: Interstate 210
Triple: [L’Auberge Casino Resort Lake Charles, locatedNear, Interstate 210]
Generated description
Interstate 210 is a bypass loop of Interstate 10 that serves the Lake Charles area in southwestern Louisiana, providing access to local destinations and easing through-traffic congestion.

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_69f224868fa8819099127eaf8855a28f completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f680da91888190b7a13f3fcbd0b71b completed May 2, 2026, 10:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7a5c6ff6c08190951e02708ae4ee46 completed Aug. 10, 2026, 11:19 p.m.
NEDg Description generation batch_6a7a5d07d04481909fe3cd43a0b8a5a6 completed Aug. 10, 2026, 11:21 p.m.
NED2 Entity disambiguation (via description) batch_6a7a5da15cf08190961d2fd165470dc7 completed Aug. 10, 2026, 11:24 p.m.
Created at: April 29, 2026, 7:45 p.m.