Triple
T3115565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Simm |
E65053
|
entity |
| Predicate | playedIn |
P2170
|
FINISHED |
| Object | Mad Dogs |
E327670
|
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: Mad Dogs | Statement: [John Simm, playedIn, Mad Dogs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mad Dogs Context triple: [John Simm, playedIn, Mad Dogs]
-
A.
Mad Dogs
chosen
Mad Dogs is a British dark comedy-drama television series about a group of middle-aged friends whose holiday in Spain spirals into crime and chaos.
-
B.
Doggumentary
Doggumentary is a studio album by American rapper Snoop Dogg that blends West Coast hip hop with diverse collaborations and themes reflecting his long-running career.
-
C.
The Dog Pound
The Dog Pound is the passionate student cheering section known for creating an energetic home-ice atmosphere at Boston University Terriers men's hockey games.
-
D.
Lawn Dogs
Lawn Dogs is a 1997 independent drama film that explores the unlikely friendship between a young girl from a wealthy family and a working-class lawn caretaker in a restrictive suburban community.
-
E.
The Dogs of War
The Dogs of War is a 1980 political war film based on Frederick Forsyth’s novel, following mercenaries hired to overthrow a fictional African dictator.
- 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_69ad857fcc088190b0c4d45a5cde6f61 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada4e40bc48190b9b17c706a2450d5 |
completed | March 8, 2026, 4:33 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f606fc881908754a78e6aa2de64 |
completed | March 12, 2026, 12:57 a.m. |
Created at: March 8, 2026, 3:04 p.m.