Triple
T97809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yankee Doodle Dandy (historical, unofficial) |
E1970
|
entity |
| Predicate | hasThematicConnection |
P494
|
FINISHED |
| Object | patriotism |
—
|
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: patriotism | Statement: [Yankee Doodle Dandy (historical, unofficial), hasThematicConnection, patriotism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThematicConnection Context triple: [Yankee Doodle Dandy (historical, unofficial), hasThematicConnection, patriotism]
-
A.
hasConcept
Indicates that an entity includes, embodies, or is associated with a particular concept.
-
B.
connectsTo
Indicates a relationship where one entity is linked or joined to another, allowing interaction, communication, or transfer between them.
-
C.
hasNotableSubject
chosen
Indicates that an entity is associated with a subject that is particularly significant, prominent, or noteworthy in relation to it.
-
D.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
E.
isAssociatedWith
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
- 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_69a24d4862f881908cc8b89d3a78031d |
completed | Feb. 28, 2026, 2:04 a.m. |
| NER | Named-entity recognition | batch_69a24feef1b08190bb9525f71cce053e |
completed | Feb. 28, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69a24ebe7b1c8190a6bfbf31dc7c7f07 |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:09 a.m.