Triple
T35766600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Åråsen farm area |
E1034031
|
entity |
| Predicate | hasLandUsedFor |
P132788
|
FINISHED |
| Object | Åråsen Stadion |
—
|
NE NERFINISHED |
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: Åråsen Stadion | Statement: [Åråsen farm area, hasLandUsedFor, Åråsen Stadion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandUsedFor Context triple: [Åråsen farm area, hasLandUsedFor, Åråsen Stadion]
-
A.
landUsedFor
chosen
Indicates that a particular area of land is utilized or designated for a specific purpose or activity.
-
B.
usedToCreateLand
Indicates that something served as a means, material, or method for producing or forming a particular piece of land.
-
C.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
D.
hasLandStatus
Indicates that an entity possesses a particular legal or administrative status regarding land (such as ownership, tenure, protection, or use designation).
-
E.
hasLandholdingsIn
Indicates that an entity owns or controls land or property located within a specified geographic area.
- 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_69f76e13edd081909101629aa829c4ad |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff97637ad881908c24fe2cc6b036db |
completed | May 9, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69ff96c43a808190942eeda1934602db |
completed | May 9, 2026, 8:19 p.m. |
Created at: May 3, 2026, 4:06 p.m.