Triple

T34352522
Position Surface form Disambiguated ID Type / Status
Subject El Vado Lake E881619 entity
Predicate near P350 FINISHED
Object Heron Lake State Park
Heron Lake State Park is a scenic New Mexico state park known for its large reservoir, boating, fishing, and wildlife viewing opportunities in a high-desert mountain setting.
E2096566 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: Heron Lake State Park | Statement: [El Vado Lake, near, Heron Lake State Park]
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: Heron Lake State Park
Triple: [El Vado Lake, near, Heron Lake State Park]
Generated description
Heron Lake State Park is a scenic New Mexico state park known for its large reservoir, boating, fishing, and wildlife viewing opportunities in a high-desert mountain setting.

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_69f349bd06008190904c2f86c42749e3 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69f713f596cc81909e25939d98f1c3e6 completed May 3, 2026, 9:23 a.m.
NED1 Entity disambiguation (via context triple) batch_6a37181e925481908b3915a7fb7be045 completed June 20, 2026, 10:45 p.m.
NEDg Description generation batch_6a3718c84ee481908c220b2564249159 completed June 20, 2026, 10:48 p.m.
NED2 Entity disambiguation (via description) batch_6a37194fcaf48190b32ef74944391ffc completed June 20, 2026, 10:50 p.m.
Created at: May 1, 2026, 1:58 a.m.