Triple
T648253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lincoln Cathedral |
E11287
|
entity |
| Predicate | hasChapterHouse |
P16489
|
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: [Lincoln Cathedral, hasChapterHouse, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChapterHouse Context triple: [Lincoln Cathedral, hasChapterHouse, yes]
-
A.
containsChapter
Indicates that one entity (typically a larger work or document) includes another entity as a chapter within its structure.
-
B.
hasCathedralChapter
chosen
Indicates that an ecclesiastical jurisdiction or church possesses or is served by a cathedral chapter as its governing or advisory body.
-
C.
hasChambersFor
Indicates that one entity contains or provides designated chambers or compartments intended for use by another entity.
-
D.
hasLocalChaptersIn
Indicates that an organization maintains one or more local chapters or branches within a specified geographic area or location.
-
E.
hasHouseSystem
Indicates that one entity possesses, uses, or is associated with a particular house system.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f308f34819094ba28cfc786051e |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0c0dcc8190849211d45489a5a7 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.