Triple
T6305158
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baron Bliss Lighthouse |
E141356
|
entity |
| Predicate | memorialPurpose |
P25987
|
FINISHED |
| Object | to honor Baron Bliss’s bequest to Belize |
—
|
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: to honor Baron Bliss’s bequest to Belize | Statement: [Baron Bliss Lighthouse, memorialPurpose, to honor Baron Bliss’s bequest to Belize]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memorialPurpose Context triple: [Baron Bliss Lighthouse, memorialPurpose, to honor Baron Bliss’s bequest to Belize]
-
A.
memorialType
Indicates the specific kind or category of memorial associated with an entity (e.g., plaque, statue, monument).
-
B.
memorialScope
Indicates the extent or boundaries of what is commemorated or covered by a memorial.
-
C.
memorialization
chosen
Indicates the act of preserving the memory or honoring the legacy of someone or something, often through a dedicated object, event, or practice.
-
D.
memorialTheme
Indicates that something (such as a work, event, or object) is dedicated to remembering, honoring, or commemorating a person, group, or event.
-
E.
hasMemorial
Indicates that a memorial exists in honor of, or dedicated to, a particular 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_69c008cf0ad4819095def81e2bd42f9f |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06479acec819090306a155a03b774 |
completed | March 22, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69c060e311b48190b1c74a5cf9435623 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:28 p.m.