Triple
T1987530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lorax (2012 film) |
E43174
|
entity |
| Predicate | voiceActor |
P1507
|
FINISHED |
| Object | Taylor Swift |
E43686
|
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: Taylor Swift | Statement: [The Lorax (2012 film), voiceActor, Taylor Swift]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taylor Swift Context triple: [The Lorax (2012 film), voiceActor, Taylor Swift]
-
A.
Taylor Swift
chosen
Taylor Swift is an American singer-songwriter known for her narrative songwriting, evolution from country to pop and indie styles, and massive global cultural and commercial impact.
-
B.
Ariana Grande
Ariana Grande is an American pop and R&B singer, songwriter, and actress known for her powerful, Mariah Carey–like vocal range and numerous chart-topping hits.
-
C.
Katy Perry
Katy Perry is an American pop singer and songwriter known for chart-topping hits like "Firework" and "Roar" and her colorful, theatrical performances.
-
D.
Taylor
Taylor is a suburban city in Wayne County, Michigan, known for its residential communities and proximity to Detroit.
-
E.
Taylor
Taylor is a common English surname borne by numerous notable individuals across fields such as politics, arts, sports, and academia.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb840a5708190a9b64564b855fb22 |
completed | March 7, 2026, 5:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae033410a88190bac79032a012549a |
completed | March 8, 2026, 11:16 p.m. |
Created at: March 4, 2026, 7:37 p.m.