Triple
T6778228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trowse Eye |
E155611
|
entity |
| Predicate | hasPhysicalContext |
P71847
|
FINISHED |
| Object | lowland river environment |
—
|
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: lowland river environment | Statement: [Trowse Eye, hasPhysicalContext, lowland river environment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhysicalContext Context triple: [Trowse Eye, hasPhysicalContext, lowland river environment]
-
A.
hasPhysicalNature
Indicates that one entity possesses or exhibits a specific physical form, composition, or material nature in relation to another.
-
B.
hasPhysicalInterface
Indicates that one entity provides or includes a tangible, hardware-based connection point or medium through which another entity can physically interact or communicate.
-
C.
hasPhysicalFootprint
Indicates that one entity occupies or affects a specific physical area or space in the real world.
-
D.
isPhysicalArtifact
Indicates that the subject is a tangible, man-made object that physically exists in the real world.
-
E.
hasNaturalContext
chosen
Indicates that something exists or occurs within a relevant real-world or naturally occurring situation or environment.
- 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_69c688162bf8819088b664b5c3b5be7a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2689d408190bc2c1ce4ae9c1b13 |
completed | March 27, 2026, 6:54 p.m. |
| PD | Predicate disambiguation | batch_69c6d095dcac8190bb9b943f50a7f885 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:13 p.m.