Triple

T31987183
Position Surface form Disambiguated ID Type / Status
Subject Dresden, Tennessee E816762 entity
Predicate locatedNearHighway P385 FINISHED
Object State Route 22
State Route 22 is a major north–south state highway in western Tennessee that connects several towns and facilitates regional travel and commerce.
 E2295967 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: State Route 22 | Statement: [Dresden, Tennessee, locatedNearHighway, State Route 22]
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: State Route 22
Triple: [Dresden, Tennessee, locatedNearHighway, State Route 22]
Generated description
State Route 22 is a major north–south state highway in western Tennessee that connects several towns and facilitates regional travel and commerce.

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_69f348f8002081909a3588758ba94afb completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6b3b1cea8819087c59b8e8016fe6d completed May 3, 2026, 2:32 a.m.
NED1 Entity disambiguation (via context triple) batch_6a82163b06dc8190b5e8d97cbdd51a79 completed Aug. 16, 2026, 7:57 p.m.
NEDg Description generation batch_6a82173ffa088190b016d6c06ce7401e completed Aug. 16, 2026, 8:02 p.m.
NED2 Entity disambiguation (via description) batch_6a82179ad8f881909245f22a1cf11785 completed Aug. 16, 2026, 8:03 p.m.
Created at: May 1, 2026, 12:12 a.m.