Triple
T37405808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cathedral Church of St Peter, Bradford |
E929126
|
entity |
| Predicate | earliestPartsDateFrom |
P78561
|
FINISHED |
| Object | 14th century |
—
|
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: 14th century | Statement: [Cathedral Church of St Peter, Bradford, earliestPartsDateFrom, 14th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earliestPartsDateFrom Context triple: [Cathedral Church of St Peter, Bradford, earliestPartsDateFrom, 14th century]
-
A.
earliestDate
Indicates the earliest point in time at which an associated event, state, or relationship is considered to begin or be valid.
-
B.
earliestVersionDate
Indicates the date on which the earliest known or first version of an entity was created, released, or became valid.
-
C.
earliestFabricDate
chosen
Indicates the earliest date at which the fabric (or material) associated with an entity was created or first produced.
-
D.
earliestSectionsDateTo
Indicates the date up to which the earliest relevant sections or segments are considered or valid in a given context.
-
E.
earliestOf
Indicates that one entity occurs or is positioned earlier in time or order than all other entities in a given set.
- 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_69f76ebbf79c8190b85bbcf3a6be57e4 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
Created at: May 3, 2026, 4:16 p.m.