Triple
T9445817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Foxworth |
E227761
|
entity |
| Predicate | portrayed |
P1668
|
FINISHED |
| Object | Chase Gioberti |
E38184
|
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: Chase Gioberti | Statement: [Robert Foxworth, portrayed, Chase Gioberti]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chase Gioberti Context triple: [Robert Foxworth, portrayed, Chase Gioberti]
-
A.
Chase Gioberti
chosen
Chase Gioberti is a central character in the 1980s American prime-time soap opera "Falcon Crest," known as a principled vineyard owner who often clashes with his powerful family over control of their wine empire.
-
B.
Preston D'Ambrosio
Preston D'Ambrosio is a fictional character appearing in the film "In Too Deep."
-
C.
Chase Stein
Chase Stein is a teenage genius and member of the Runaways in Marvel Comics, known for his engineering skills and use of advanced technology and weapons.
-
D.
Trenton Fisher
Trenton Fisher is known as the husband of American singer Kate Smith.
-
E.
Garrett Snyder
Garrett Snyder is a food writer and journalist known for co-authoring "The Pepper Thai Cookbook" with Pepper Teigen.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f33deb88190bc74968575963ac4 |
completed | April 1, 2026, 8:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1225df53c819091b64f8cda159ae9 |
completed | April 4, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:51 p.m.