Triple
T19044102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abbaye-aux-Dames, Caen |
E466083
|
entity |
| Predicate | hasConventBuildings |
P122205
|
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: [Abbaye-aux-Dames, Caen, hasConventBuildings, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConventBuildings Context triple: [Abbaye-aux-Dames, Caen, hasConventBuildings, yes]
-
A.
hasConvent
chosen
Indicates that an entity possesses, contains, or is associated with a convent.
-
B.
hasClericalStructure
Indicates that an entity possesses an organized clerical or administrative hierarchy or framework.
-
C.
hasMunicipalBuildings
Indicates that a place or jurisdiction possesses one or more buildings used for municipal or local government functions.
-
D.
hasCathedralType
Indicates that an entity is associated with, classified by, or designated as having a specific type or category of cathedral.
-
E.
hasProCathedral
Indicates that one entity serves as or possesses a pro-cathedral (a church temporarily acting as a cathedral) in relation to another entity.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d802a75c8190a4ce45e5fbffc1b7 |
completed | April 20, 2026, 7:38 a.m. |
| PD | Predicate disambiguation | batch_69e4b99633c8819097988608c278ecf8 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:03 p.m.