Triple
T14958107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Hannigan |
E372985
|
entity |
| Predicate | sings |
P12693
|
FINISHED |
| Object | Easy Street |
E147986
|
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: Easy Street | Statement: [Miss Hannigan, sings, Easy Street]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Easy Street Context triple: [Miss Hannigan, sings, Easy Street]
-
A.
Easy Street
Easy Street is a locality or feature situated beside the Easy Street Basin, likely serving as an access route or boundary area for the basin.
-
B.
Easy Street
Easy Street is an American sitcom best known for starring Loni Anderson in a comedic role during the 1980s.
-
C.
Easy Street
chosen
"Easy Street" is a 1917 silent comedy film directed by and starring Charlie Chaplin as his iconic Tramp character.
-
D.
Paradise City
"Paradise City" is a popular hard rock song by Guns N' Roses, known for its anthemic chorus and prominent place on their debut album Appetite for Destruction.
-
E.
Beat Street
Beat Street is a 1984 American drama film centered on New York City’s early hip-hop culture, including breakdancing, DJing, and graffiti art.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6cd85bc81909040b7ff78f62554 |
completed | April 15, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e9e74fc8190bdd10a25c39829f3 |
completed | May 9, 2026, 12:23 a.m. |
Created at: April 10, 2026, 2:40 a.m.