Triple
T14963958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert H. Treman |
E373137
|
entity |
| Predicate | hasParticularInterestIn |
P66206
|
FINISHED |
| Object | protection of natural landscapes |
—
|
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: protection of natural landscapes | Statement: [Robert H. Treman, hasParticularInterestIn, protection of natural landscapes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasParticularInterestIn Context triple: [Robert H. Treman, hasParticularInterestIn, protection of natural landscapes]
-
A.
subjectInterest
chosen
Indicates that the subject has an interest in, or is concerned with, the object.
-
B.
hasScientificInterestIn
Indicates that one entity holds a scientific curiosity, concern, or research focus directed toward another entity.
-
C.
primaryInterest
Indicates that one entity is the main or most significant focus of attention, concern, or engagement for another entity.
-
D.
hasAreaOfInterest
Indicates that an entity possesses or is associated with a particular area of interest or focus.
-
E.
collectorInterest
Indicates that one entity has a special interest in acquiring, owning, or seeking out another entity as part of a collection.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6d0487c8190b7754af8c5014b37 |
completed | April 15, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69de9a5d995881909e33658f5aea5582 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:40 a.m.