Triple
T35189809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raynell Maxson |
E1016088
|
entity |
| Predicate | symbolizesForCory |
P183169
|
FINISHED |
| Object | reason to reconsider attending Troy’s funeral |
—
|
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: reason to reconsider attending Troy’s funeral | Statement: [Raynell Maxson, symbolizesForCory, reason to reconsider attending Troy’s funeral]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolizesForCory Context triple: [Raynell Maxson, symbolizesForCory, reason to reconsider attending Troy’s funeral]
-
A.
symbolizes
Indicates that one entity stands for, represents, or is used as a sign for another entity, concept, or idea.
-
B.
symbolizedIn
Indicates that one entity serves as a symbol or representation of another entity.
-
C.
shapeSymbolism
Indicates how a particular shape is associated with or conveys symbolic meaning within a given context.
-
D.
ceremonialSymbol
Indicates that one entity serves as a symbol used in a formal or ritual ceremony for another entity or concept.
-
E.
languageOfSymbolism
Indicates that one entity is the language in which the symbolic meaning or symbolism of another entity is expressed or encoded.
- 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_69f76ddd815c8190b822eea06630f9fb |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f798387ea481909f51303f53a22e52 |
completed | May 3, 2026, 6:47 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
| PDg | Predicate description generation | batch_69f79798663481908d6bc48dd6a94ca6 |
completed | May 3, 2026, 6:44 p.m. |
Created at: May 3, 2026, 4:02 p.m.