Triple
T30959567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayor Aloysius O'Hare |
E788769
|
entity |
| Predicate | themeSymbolized |
P55707
|
FINISHED |
| Object | corporate greed |
—
|
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: corporate greed | Statement: [Mayor Aloysius O'Hare, themeSymbolized, corporate greed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: themeSymbolized Context triple: [Mayor Aloysius O'Hare, themeSymbolized, corporate greed]
-
A.
themeRepresentation
chosen
Indicates that one entity serves as a representation, depiction, or expression of the thematic content associated with another entity.
-
B.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
C.
shapeSymbolism
Indicates how a particular shape is associated with or conveys symbolic meaning within a given context.
-
D.
emblemSymbolism
Indicates that one entity serves as an emblem whose design or features symbolically represent or convey meanings about another entity.
-
E.
themeCharacteristic
Indicates that a characteristic, quality, or property is attributed to or associated with a particular theme.
- 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_69f224c28c1881908c33b45d689f1724 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ef92308190903a54fc74233269 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:54 p.m.