Triple

T17900816
Position Surface form Disambiguated ID Type / Status
Subject Forest County, Pennsylvania E447570 entity
Predicate hasPublicLand P41739 FINISHED
Object federal land LITERAL 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: federal land | Statement: [Forest County, Pennsylvania, hasPublicLand, federal land]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasPublicLand
Context triple: [Forest County, Pennsylvania, hasPublicLand, federal land]
  • A. isPublicLand
    Indicates that a given area of land is owned or managed by a government or public authority and is accessible or designated for use by the general public.
  • B. hasNearbyPublicLand
    Indicates that one entity is located close to an area of public land, such as parks, reserves, or other publicly accessible open spaces.
  • C. hasExtensivePublicLands
    Indicates that a place or jurisdiction possesses a large amount of land designated for public use, such as parks, forests, or other publicly managed open spaces.
  • D. hasLandStatus chosen
    Indicates that an entity possesses a particular legal or administrative status regarding land (such as ownership, tenure, protection, or use designation).
  • E. percentagePublicLand
    Indicates the proportion of land within a given area that is owned or managed by public authorities rather than private entities.
  • F. None of above.

Provenance (3 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_69d8b9f59bd48190a6fc925a855b8bac completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49d8321bc8190a3f679d96323cbbb completed April 19, 2026, 9:16 a.m.
PD Predicate disambiguation batch_69e3d8e9b77c8190bbfb508f28dfacfa completed April 18, 2026, 7:18 p.m.
Created at: April 10, 2026, 10:19 a.m.