Triple
T2115708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stowe School |
E43803
|
entity |
| Predicate | originalUseOfCampus |
P34899
|
FINISHED |
| Object | country house |
—
|
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: country house | Statement: [Stowe School, originalUseOfCampus, country house]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalUseOfCampus Context triple: [Stowe School, originalUseOfCampus, country house]
-
A.
campusUse
Indicates that something is intended for, associated with, or occurring in the use or activities of a campus or campus community.
-
B.
campusLaterUsedFor
Indicates that a particular campus was subsequently repurposed or occupied for a different use at a later time.
-
C.
formerCampus
Indicates that an entity was once located on or associated with a particular campus, but is no longer based there.
-
D.
cityCampus
Indicates that a campus is located within or associated with a particular city.
-
E.
campus
Indicates that an entity is located on, associated with, or taking place within a particular campus.
- F. None of above. chosen
Provenance (4 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb0724e08190a0a4210d86261d6d |
completed | March 7, 2026, 5:43 a.m. |
| PD | Predicate disambiguation | batch_69abb7bbf9d881909d223b0cab7cab18 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb85fe7a08190b991b1f23bc34f93 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:43 p.m.