Triple
T24154201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Lurie |
E598628
|
entity |
| Predicate | associatedWithAnimalSymbolism |
P41568
|
FINISHED |
| Object | dogs at the animal clinic |
—
|
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: dogs at the animal clinic | Statement: [David Lurie, associatedWithAnimalSymbolism, dogs at the animal clinic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithAnimalSymbolism Context triple: [David Lurie, associatedWithAnimalSymbolism, dogs at the animal clinic]
-
A.
animalSymbol
chosen
Indicates that one entity serves as a symbolic representation or emblem of the other in the form of an animal.
-
B.
fieldSymbolism
Indicates the symbolic meaning or thematic associations that a field (as a setting, area, or domain) conveys within a given context.
-
C.
shapeSymbolism
Indicates how a particular shape is associated with or conveys symbolic meaning within a given context.
-
D.
languageOfSymbolism
Indicates that one entity is the language in which the symbolic meaning or symbolism of another entity is expressed or encoded.
-
E.
treeSymbolism
Indicates the use of a tree as a symbolic representation of an idea, quality, or relationship between entities.
- 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_69e288cb0a3081909ef221744f274384 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e0e4372081909d2b3f7f2af7b407 |
completed | April 29, 2026, 10:43 a.m. |
| PD | Predicate disambiguation | batch_69f176585f3481909beb907de252cd98 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:31 p.m.