Triple
T4972423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brox Burn |
E111684
|
entity |
| Predicate | hasLocalUse |
P43475
|
FINISHED |
| Object | drainage for surrounding 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: drainage for surrounding land | Statement: [Brox Burn, hasLocalUse, drainage for surrounding land]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalUse Context triple: [Brox Burn, hasLocalUse, drainage for surrounding land]
-
A.
hasTypicalUsageRegion
Indicates that something is most commonly or characteristically used within a particular geographic region.
-
B.
hasLocalInstitution
Indicates that a given place or region possesses or hosts an institution that operates locally within its boundaries.
-
C.
hasLandUseCharacter
chosen
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
D.
hasHumanUse
Indicates that something is used, employed, or utilized by humans for a particular purpose or benefit.
-
E.
isLocalQuantity
Indicates that a quantity is specific to a particular context, location, or subsystem rather than being globally applicable.
- 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_69bd441a0eb481908050fa4273b19eae |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd7146e6e881908a55ab2756b631f6 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:33 p.m.