Triple
T20624899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Let the Dominoes Fall |
E506791
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | New Orleans |
—
|
NE NERFINISHED |
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: New Orleans | Statement: [Let the Dominoes Fall, hasPart, New Orleans]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: New Orleans Context triple: [Let the Dominoes Fall, hasPart, New Orleans]
-
A.
New Orleans
chosen
New Orleans is a historic port city in southeastern Louisiana known for its vibrant jazz music, Creole cuisine, and distinctive French and Spanish-influenced architecture.
-
B.
City of New Orleans
City of New Orleans is a famous long-distance passenger train that runs between Chicago and New Orleans and was popularized by the folk song of the same name.
-
C.
Nola
Nola is an ancient town in southern Italy, historically significant in Roman times and known as the place where Emperor Augustus died.
-
D.
Baton Rouge, Louisiana
Baton Rouge, Louisiana is the capital city of Louisiana, known for its role as a political, industrial, and cultural center along the Mississippi River.
-
E.
Shreveport
Shreveport is a major city in northwestern Louisiana known for its role as a regional commercial, cultural, and transportation hub.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4bc90988190ac360aaf645efc1d |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe3d76c8190a8a5cb52bb9bfc2b |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:42 a.m.