Triple

T30930103
Position Surface form Disambiguated ID Type / Status
Subject Battle of Rain E787969 entity
Predicate tookPlaceNear P350 FINISHED
Object town of Rain am Lech
The town of Rain am Lech is a Bavarian settlement in southern Germany, historically notable as the site of a major Thirty Years' War battle.
 E1938578 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: town of Rain am Lech | Statement: [Battle of Rain, tookPlaceNear, town of Rain am Lech]
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: town of Rain am Lech
Triple: [Battle of Rain, tookPlaceNear, town of Rain am Lech]
Generated description
The town of Rain am Lech is a Bavarian settlement in southern Germany, historically notable as the site of a major Thirty Years' War battle.

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_69f224c0b7fc819090cb89df60d23653 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f692e0113c8190b5b207b7e5182ee0 completed May 3, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28e4722f7081909a27c6242d7edfe1 completed June 10, 2026, 4:13 a.m.
NEDg Description generation batch_6a28e8725e1c8190aa67407dd30526f0 completed June 10, 2026, 4:30 a.m.
NED2 Entity disambiguation (via description) batch_6a28e8fe05b48190a85b891563c69c45 completed June 10, 2026, 4:33 a.m.
Created at: April 29, 2026, 8:52 p.m.