Triple

T26532212
Position Surface form Disambiguated ID Type / Status
Subject Great North Woods E670847 entity
Predicate hasMajorLake P1025 FINISHED
Object Lake Francis
Lake Francis is a prominent freshwater lake in New Hampshire’s remote Great North Woods region, known for its scenic wilderness setting and outdoor recreation opportunities.
 E1771543 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: Lake Francis | Statement: [Great North Woods, hasMajorLake, Lake Francis]
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: Lake Francis
Triple: [Great North Woods, hasMajorLake, Lake Francis]
Generated description
Lake Francis is a prominent freshwater lake in New Hampshire’s remote Great North Woods region, known for its scenic wilderness setting and outdoor recreation opportunities.

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_69eeb31ea1e08190b9ff43cf9bc25bf8 completed April 27, 2026, 12:51 a.m.
NER Named-entity recognition batch_69f613f84cdc8190828985c94d8491d5 completed May 2, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b214240c8190a46f9b624bdd82c9 completed May 24, 2026, 8:08 a.m.
NEDg Description generation batch_6a12b2951f848190bddd5bbf7d6bc73b completed May 24, 2026, 8:11 a.m.
NED2 Entity disambiguation (via description) batch_6a12b33dc9f881908cca1fd1b03c6c67 completed May 24, 2026, 8:13 a.m.
Created at: April 27, 2026, 1:36 a.m.