Triple
T21011192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "L.A L.A" |
E517550
|
entity |
| Predicate | responseTo |
P1128
|
FINISHED |
| Object | "New York, New York" |
—
|
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 York, New York" | Statement: ["L.A L.A", responseTo, "New York, New York"]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: "New York, New York" Context triple: ["L.A L.A", responseTo, "New York, New York"]
-
A.
“New York, New York”
chosen
“New York, New York” is a classic American song, famously performed by Frank Sinatra, that has become an iconic anthem celebrating the city of New York.
-
B.
“N.Y.C.”
“N.Y.C.” is likely a track or component piece associated with the musical work or project titled “Mamouna.”
-
C.
"Manhattan"
"Manhattan" is a classic 1925 popular song by Richard Rodgers and Lorenz Hart that wittily romanticizes New York City's borough of Manhattan.
-
D.
“Down in New York City”
“Down in New York City” is a track from The Weatherman LP by American singer-songwriter Gregory Alan Isakov.
-
E.
The Big Apple
The Big Apple is a famous nickname for New York City, evoking its status as a major global center of culture, finance, and entertainment.
- 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_69e0b50192308190a284fcc89dd23a49 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc3fdf3c8190abd3db7f5eb503a0 |
completed | April 21, 2026, 4:25 a.m. |
Created at: April 16, 2026, 1:53 p.m.