Triple
T14629159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rodgers and Hart |
E343433
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Where or When |
E628233
|
NE 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: Where or When | Statement: [Rodgers and Hart, notableWork, Where or When]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Where or When Context triple: [Rodgers and Hart, notableWork, Where or When]
-
A.
Where or When
chosen
"Where or When" is a popular show tune by Richard Rodgers and Lorenz Hart that became a standard after its introduction in the 1937 musical *Babes in Arms*.
-
B.
How When and Where
"How When and Where" is a song featured on Shakira's album "Las Mujeres Ya No Lloran."
-
C.
Where It's At
"Where It's At" is a Grammy-winning alternative rock song by Beck, known for its eclectic sampling, catchy chorus, and role in defining his breakthrough 1996 album *Odelay*.
-
D.
Cómo Dónde y Cuándo
"Cómo Dónde y Cuándo" is a Spanish-language pop song by Shakira featured on her album "Las Mujeres Ya No Lloran."
-
E.
Whereabouts
Whereabouts is a reflective, introspective novel by Jhumpa Lahiri that follows an unnamed woman navigating solitude and everyday life in an unnamed Italian city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d822dffc3c8190aa173b90761bffda |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4a7c8fc81909d10c1f563d7d1e7 |
completed | April 14, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda92ded848190b031d3ff29e54a00 |
completed | May 8, 2026, 9:13 a.m. |
Created at: April 10, 2026, 1:26 a.m.