Triple

T37271593
Position Surface form Disambiguated ID Type / Status
Subject Bastrop State Park E924527 entity
Predicate hasTrail P3625 FINISHED
Object Lost Pines Trail
Lost Pines Trail is a hiking path in Bastrop State Park, Texas, known for winding through the region’s distinctive loblolly pine forest often called the “Lost Pines.”
 E2223299 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: Lost Pines Trail | Statement: [Bastrop State Park, hasTrail, Lost Pines Trail]
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: Lost Pines Trail
Triple: [Bastrop State Park, hasTrail, Lost Pines Trail]
Generated description
Lost Pines Trail is a hiking path in Bastrop State Park, Texas, known for winding through the region’s distinctive loblolly pine forest often called the “Lost Pines.”

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_69f76eacdd8c819094080d3991e6d37c completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb5aa1f28881909d0f7eaf85c9692b completed May 6, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a406ccaf0c081909f777dc3dfa43361 completed June 28, 2026, 12:37 a.m.
NEDg Description generation batch_6a406db565b881909769124848e2b508 completed June 28, 2026, 12:41 a.m.
NED2 Entity disambiguation (via description) batch_6a406e2e5e00819097b90719f08951c8 completed June 28, 2026, 12:43 a.m.
Created at: May 3, 2026, 4:15 p.m.