Triple
T38012210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Laurence |
E948393
|
entity |
| Predicate | hasChurchesDedicatedIn |
P199652
|
FINISHED |
| Object | England |
—
|
NE NERFINISHED |
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: England | Statement: [St Laurence, hasChurchesDedicatedIn, England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChurchesDedicatedIn Context triple: [St Laurence, hasChurchesDedicatedIn, England]
-
A.
hasParishChurchDedication
Indicates that a parish church is dedicated to, or placed under the patronage of, a particular figure, saint, or sacred concept.
-
B.
hasChurch
Indicates that a place or entity possesses, contains, or is associated with a church.
-
C.
hasCoCathedralDedication
Indicates that a co-cathedral is formally dedicated to or in honor of a particular figure, concept, or sacred subject.
-
D.
hasNumberOfChurches
Indicates the relationship that specifies how many churches are associated with a given entity.
-
E.
hadTempleDedicatedTo
Indicates that a temple was formally dedicated in honor of, or for the worship of, a particular entity.
- 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_69f76efb4b10819092c8c2ba28ac06a8 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69ff49f888348190b9c55afa73b99e6a |
completed | May 9, 2026, 2:51 p.m. |
| PD | Predicate disambiguation | batch_69ff49614ef88190ac70b034c55ad738 |
completed | May 9, 2026, 2:49 p.m. |
| PDg | Predicate description generation | batch_69ff49f7db2c819094d488d13985334c |
completed | May 9, 2026, 2:51 p.m. |
Created at: May 3, 2026, 4:20 p.m.