Triple
T319960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winchester College |
E7791
|
entity |
| Predicate | hasHouseSystem |
P12424
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Winchester College, hasHouseSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHouseSystem Context triple: [Winchester College, hasHouseSystem, yes]
-
A.
hasHouse
Indicates that one entity possesses, owns, or is provided with a house in relation to another entity.
-
B.
hasNumberOfHouses
Indicates the quantity of houses associated with a given entity.
-
C.
hasManorHouse
Indicates that one entity possesses or is associated with a manor house as a property or feature.
-
D.
hasCorrelativesSystem
Indicates that one entity possesses or employs a system of correlatives—structured, corresponding elements or forms that are systematically related to each other.
-
E.
hasNumberSystem
Indicates that an entity possesses or uses a particular system for representing and organizing numbers.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ea7edbc48190b9031bd1af48f72a |
completed | Feb. 28, 2026, 1:15 p.m. |
| PD | Predicate disambiguation | batch_69a2e946607081909c8b97473aaf8d1b |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea7d03a88190aab72e61d8673488 |
completed | Feb. 28, 2026, 1:15 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.