Triple
T18913792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bedford Chapel |
E462671
|
entity |
| Predicate | hasBurialMonumentType |
P133766
|
FINISHED |
| Object | alabaster effigies |
—
|
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: alabaster effigies | Statement: [Bedford Chapel, hasBurialMonumentType, alabaster effigies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBurialMonumentType Context triple: [Bedford Chapel, hasBurialMonumentType, alabaster effigies]
-
A.
hasTypeOfBurial
Indicates the specific kind or method of burial associated with an entity.
-
B.
hasBurialVault
Indicates that an entity possesses or is associated with a specific burial vault used for interment or storage of remains.
-
C.
hasMausoleum
Indicates that one entity possesses, contains, or is associated with a mausoleum dedicated to another entity.
-
D.
hasTypeOfGrave
Indicates that an entity is associated with a specific kind or category of grave.
-
E.
hasTombDesignation
Indicates that an entity has been assigned a specific formal designation or identifier for its tomb.
- 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_69d8dcfdbbb881909964fa5a75bd0b48 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c625b4fc8190a9dda6e76afa573e |
completed | April 20, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e9e6488190ba8df92c8058ed88 |
completed | April 19, 2026, 9:39 a.m. |
| PDg | Predicate description generation | batch_69e4ad8e075c8190ad561edc5e520057 |
completed | April 19, 2026, 10:25 a.m. |
Created at: April 10, 2026, 11:58 a.m.