Triple
T27045910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry W. Coe State Park |
E684625
|
entity |
| Predicate | hasPreviousLandUse |
P44099
|
FINISHED |
| Object | ranchlands |
—
|
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: ranchlands | Statement: [Henry W. Coe State Park, hasPreviousLandUse, ranchlands]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPreviousLandUse Context triple: [Henry W. Coe State Park, hasPreviousLandUse, ranchlands]
-
A.
formerLandUse
chosen
Indicates the type of land use that characterized a location prior to its current or present use.
-
B.
hasHistoricalLandCover
Indicates that an entity is associated with information about the land cover that existed in a specified area during a past time period.
-
C.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
D.
hasLikelyLandUse
Indicates that an area or parcel is associated with a predicted or most probable type of land use (e.g., residential, commercial, agricultural).
-
E.
previousBuildingUse
Indicates that a building previously served a specified use or function before its current one.
- 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_69ef148193c48190bb1a0cfae6a407c4 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69fd82ed2a4c81908bd7797fbd2e3d08 |
completed | May 8, 2026, 6:30 a.m. |
| PD | Predicate disambiguation | batch_69fd814cc10481908e4f8123d35a5d0c |
completed | May 8, 2026, 6:23 a.m. |
Created at: April 27, 2026, 8:09 a.m.