Triple
T29273808
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carry On Sergeant |
E742193
|
entity |
| Predicate | characterPlayedBy Kenneth Connor |
P193601
|
FINISHED |
| Object | Horace Strong |
—
|
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: Horace Strong | Statement: [Carry On Sergeant, characterPlayedBy Kenneth Connor, Horace Strong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterPlayedBy Kenneth Connor Context triple: [Carry On Sergeant, characterPlayedBy Kenneth Connor, Horace Strong]
-
A.
characterPlayedByRichardHarris
Indicates that the subject is a character that was portrayed by the actor Richard Harris.
-
B.
characterPlayedByRobertPatrick
Indicates that a given character is portrayed or acted by Robert Patrick.
-
C.
characterPlayedBy Bob Monkhouse
Indicates that a character is portrayed or acted by Bob Monkhouse.
-
D.
characterPlayedByIainGlen
Indicates that the subject is a character portrayed or voiced by the actor Iain Glen.
-
E.
characterPlayedByEdwardMulhare
Indicates that the subject is a character that was portrayed or played by Edward Mulhare.
- F. None of above. chosen
Provenance (4 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_69f0912124d48190a046642b69407f4c |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69fd4d1854988190be093b103a681798 |
completed | May 8, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69fd4c8d1a188190897c24527337814a |
completed | May 8, 2026, 2:38 a.m. |
| PDg | Predicate description generation | batch_69fd4d16dd20819096957c40f43cd971 |
completed | May 8, 2026, 2:40 a.m. |
Created at: April 28, 2026, 12:49 p.m.