Triple
T3787359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yizkor memorial service |
E85559
|
entity |
| Predicate | memorialScope |
P51520
|
FINISHED |
| Object | deceased parents |
—
|
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: deceased parents | Statement: [Yizkor memorial service, memorialScope, deceased parents]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memorialScope Context triple: [Yizkor memorial service, memorialScope, deceased parents]
-
A.
memorialization
Indicates the act of preserving the memory or honoring the legacy of someone or something, often through a dedicated object, event, or practice.
-
B.
memorialType
Indicates the specific kind or category of memorial associated with an entity (e.g., plaque, statue, monument).
-
C.
hasMemorial
Indicates that a memorial exists in honor of, or dedicated to, a particular entity.
-
D.
relatedMemorial
Indicates a relationship where one entity serves as a memorial or commemorative reference to another entity.
-
E.
memorializesDeathsDuring
Indicates a relationship in which something serves as a memorial specifically for deaths that occurred during a particular event, period, or circumstance.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee634c6ac819099653c660c286746 |
completed | March 9, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69aee3d3c92c819081d9d5c45ef37a5d |
completed | March 9, 2026, 3:14 p.m. |
| PDg | Predicate description generation | batch_69aee633dab88190b14cec8afb19ca6a |
completed | March 9, 2026, 3:24 p.m. |
Created at: March 9, 2026, 3:13 p.m.