Triple
T20558563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penn Badgley |
E504784
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Badgley |
—
|
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: Badgley | Statement: [Penn Badgley, familyName, Badgley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Badgley Context triple: [Penn Badgley, familyName, Badgley]
-
A.
Burdines
Burdines was a Florida-based department store chain known for its prominent presence in the state’s retail landscape before being absorbed into the Macy’s brand.
-
B.
Marchesa
Marchesa is the Italian noble title traditionally used to designate a woman holding the rank of marquess.
-
C.
Marchesa
Marchesa is a luxury fashion label renowned for its ornate, red-carpet-ready eveningwear and bridal gowns.
-
D.
Burch
chosen
Burch is a surname of English origin borne by various notable individuals across politics, arts, and other fields.
-
E.
Halston
Halston is a biographical drama miniseries that chronicles the rise and fall of the iconic American fashion designer Roy Halston Frowick.
- 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_69e0b4b6587c8190aee63dc7cff244ea |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a5e178648190910795bae5422e50 |
completed | April 20, 2026, 10:17 p.m. |
Created at: April 16, 2026, 11:38 a.m.