Triple

T27362812
Position Surface form Disambiguated ID Type / Status
Subject Intercourse, Pennsylvania E685873 entity
Predicate locatedIn P40 FINISHED
Object Leacock Township
Leacock Township is a rural municipality in Lancaster County, Pennsylvania, known for its Amish communities and for encompassing the village of Intercourse, a popular tourist destination.
E1843591 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: Leacock Township | Statement: [Intercourse, Pennsylvania, locatedIn, Leacock Township]
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: Leacock Township
Triple: [Intercourse, Pennsylvania, locatedIn, Leacock Township]
Generated description
Leacock Township is a rural municipality in Lancaster County, Pennsylvania, known for its Amish communities and for encompassing the village of Intercourse, a popular tourist destination.

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_69ef14887c288190931b8431fdbf53c4 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62c24f5388190ae16556dbd7cd664 completed May 2, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2505847ee0819098ea167ef36ce07e completed June 7, 2026, 5:45 a.m.
NEDg Description generation batch_6a250a1a410c8190a68a4be8711903c5 completed June 7, 2026, 6:05 a.m.
NED2 Entity disambiguation (via description) batch_6a250a9d57948190bd23291cc4373a77 completed June 7, 2026, 6:07 a.m.
Created at: April 27, 2026, 11:54 a.m.