Triple
T16098334
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CHiPs |
E390544
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Erik Estrada |
E1104560
|
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: Erik Estrada | Statement: [CHiPs, portrayedBy, Erik Estrada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Erik Estrada Context triple: [CHiPs, portrayedBy, Erik Estrada]
-
A.
Erik Estrada
chosen
Erik Estrada is an American actor best known for his role as Officer Frank Poncherello on the television series "CHiPs."
-
B.
Erik-Michael Estrada
Erik-Michael Estrada is an American singer and performer best known as a founding member of the early 2000s boy band O-Town, formed on the reality TV show "Making the Band."
-
C.
Hector Elizondo
Hector Elizondo is an American character actor known for his versatile roles in film and television, including frequent collaborations with director Garry Marshall in movies like "Pretty Woman" and "The Princess Diaries."
-
D.
Greg Garcia
Greg Garcia is an American television writer and producer best known for creating the sitcom "My Name Is Earl."
-
E.
Joe Garza
Joe Garza is a relatively obscure individual whose name is shared with several people, including professionals in fields such as law, politics, and the arts.
- 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_69d87f198bc48190a8b7e53ca15b7ead |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e1ff6551a48190afb7e0c61e22b541 |
completed | April 17, 2026, 9:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeb9b3e708190be822f7ed588c9da |
completed | May 10, 2026, 2:21 a.m. |
Created at: April 10, 2026, 4:59 a.m.