Triple
T19300857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mae West |
E482689
|
entity |
| Predicate | starredIn |
P1668
|
FINISHED |
| Object | Goin’ to Town |
—
|
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: Goin’ to Town | Statement: [Mae West, starredIn, Goin’ to Town]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Goin’ to Town Context triple: [Mae West, starredIn, Goin’ to Town]
-
A.
Goin' to Town
chosen
"Goin' to Town" is a 1935 American comedy film starring Mae West, known for its witty dialogue and West's trademark bold, comedic persona.
-
B.
Trouble in Town
"Trouble in Town" is a politically charged, atmospheric rock song by Coldplay that reflects on social injustice and urban tension.
-
C.
Nights in Town
"Nights in Town" is a collection of vivid, atmospheric stories by Thomas Burke that portray the lives and underbelly of urban London.
-
D.
My Kind of Town
"My Kind of Town" is a popular American song, famously performed by Frank Sinatra, that celebrates the city of Chicago and has become a classic of the Great American Songbook.
-
E.
My Kind of Town
"My Kind of Town" is a work associated with actor Nadim Sawalha, likely a film or television project in which he played a significant role.
- 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_69d8e8d04d5c8190baa816986f2b1d1e |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fc8a2a5c8190bfe95e40d3c93a42 |
completed | April 20, 2026, 10:14 a.m. |
Created at: April 10, 2026, 1:31 p.m.