Triple
T8874310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ray Danton |
E211233
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The Mod Squad |
E230839
|
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: The Mod Squad | Statement: [Ray Danton, notableWork, The Mod Squad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Mod Squad Context triple: [Ray Danton, notableWork, The Mod Squad]
-
A.
The Mod Squad
chosen
The Mod Squad is an American television crime drama series from the late 1960s and early 1970s that followed three young undercover cops working to infiltrate the counterculture.
-
B.
Sanford and Son
Sanford and Son is a classic 1970s American sitcom about a cantankerous junk dealer and his long-suffering son, renowned for its sharp humor and cultural impact.
-
C.
Bel-Air
Bel-Air is a Paris Métro station located in the 12th arrondissement of Paris, France.
-
D.
Bel-Air
Bel-Air is an upscale residential and commercial barangay in Makati City, Metro Manila, known for its gated villages and proximity to the central business district.
-
E.
Bel-Air
Bel-Air is a central public transport interchange in Geneva, Switzerland, serving as a key node for tram and bus connections across the city.
- 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_69ca838e78748190934d82db3104f855 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc614451d081908804430a72d00edf |
completed | April 1, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfa0f9714c8190909587eecbb10e1a |
completed | April 3, 2026, 11:14 a.m. |
Created at: March 30, 2026, 6:52 p.m.