Triple

T27550663
Position Surface form Disambiguated ID Type / Status
Subject Mount Tamalpais Watershed E695488 entity
Predicate contains P35 FINISHED
Object Bon Tempe Lake
Bon Tempe Lake is a popular reservoir in Marin County, California, known for its fishing, hiking trails, and scenic views within the Mount Tamalpais Watershed.
E1919847 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: Bon Tempe Lake | Statement: [Mount Tamalpais Watershed, contains, Bon Tempe Lake]
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: Bon Tempe Lake
Triple: [Mount Tamalpais Watershed, contains, Bon Tempe Lake]
Generated description
Bon Tempe Lake is a popular reservoir in Marin County, California, known for its fishing, hiking trails, and scenic views within the Mount Tamalpais Watershed.

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_69ef5386c3e08190bfe33aa326e1f72b completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62f89747c8190b89871e039647806 completed May 2, 2026, 5:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27be472cb08190a04fd8cf631a03a9 completed June 9, 2026, 7:18 a.m.
NEDg Description generation batch_6a27c1e7e08881909adc8884524ff1f2 completed June 9, 2026, 7:34 a.m.
NED2 Entity disambiguation (via description) batch_6a27c56068d88190ac70d4300b5a1cad completed June 9, 2026, 7:48 a.m.
Created at: April 27, 2026, 1:34 p.m.