Triple

T33147452
Position Surface form Disambiguated ID Type / Status
Subject Buckingham Township, Bucks County, Pennsylvania E848340 entity
Predicate contains P35 FINISHED
Object Lahaska Creek
Lahaska Creek is a small stream in Bucks County, Pennsylvania, that flows through rural and suburban areas of Buckingham Township and its surroundings.
E2296725 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: Lahaska Creek | Statement: [Buckingham Township, Bucks County, Pennsylvania, contains, Lahaska Creek]
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: Lahaska Creek
Triple: [Buckingham Township, Bucks County, Pennsylvania, contains, Lahaska Creek]
Generated description
Lahaska Creek is a small stream in Bucks County, Pennsylvania, that flows through rural and suburban areas of Buckingham Township and its surroundings.

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_69f3495a458c8190a1d34b237ba0be3f completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6d88ffa6081909b64a7014108abc7 completed May 3, 2026, 5:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a82aa4929a88190a127e3dda1b4aba5 completed Aug. 17, 2026, 6:29 a.m.
NEDg Description generation batch_6a82aaac39a88190b86f957092368c86 completed Aug. 17, 2026, 6:31 a.m.
NED2 Entity disambiguation (via description) batch_6a82ab07c1848190b2afc4c5e23b116c completed Aug. 17, 2026, 6:32 a.m.
Created at: May 1, 2026, 1:28 a.m.