Triple
T20232523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Logopolis |
E495562
|
entity |
| Predicate | featuresActor |
P15562
|
FINISHED |
| Object | Tom Baker |
—
|
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: Tom Baker | Statement: [Logopolis, featuresActor, Tom Baker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Baker Context triple: [Logopolis, featuresActor, Tom Baker]
-
A.
Tom Baker
chosen
Tom Baker is a British actor best known for his iconic portrayal of the Fourth Doctor in the long-running science fiction television series "Doctor Who."
-
B.
Tom Baker
Tom Baker is the harried but loving father of twelve children in the family comedy film "Cheaper by the Dozen."
-
C.
Jon Pertwee
Jon Pertwee was a British actor best known for playing the Third Doctor in the long-running science fiction television series Doctor Who.
-
D.
Sylvester McCoy
Sylvester McCoy is a Scottish actor best known for playing the Seventh Doctor in the long-running British science fiction series "Doctor Who."
-
E.
Peter Davison
Peter Davison is a British actor best known for playing the Fifth Doctor in the long-running science fiction television series Doctor Who.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e67166d4d081908c4b8eeb66e7e090 |
completed | April 20, 2026, 6:33 p.m. |
Created at: April 11, 2026, 11:40 p.m.