Triple
T29140700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Morecambe & Wise Show (appearances) |
E738622
|
entity |
| Predicate | featuresDoubleAct |
P199103
|
FINISHED |
| Object | Morecambe and Wise |
—
|
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: Morecambe and Wise | Statement: [The Morecambe & Wise Show (appearances), featuresDoubleAct, Morecambe and Wise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresDoubleAct Context triple: [The Morecambe & Wise Show (appearances), featuresDoubleAct, Morecambe and Wise]
-
A.
featuresDualRole
Indicates that an entity simultaneously fulfills two distinct roles or functions within a given context.
-
B.
featuresProductionDuo
Indicates that an entity includes or prominently involves a specific production duo in its creation or presentation.
-
C.
portraysDoubleRole
Indicates that a single performer or entity depicts or assumes two distinct roles within the same context or work.
-
D.
hasTwinActors
Indicates that two or more actors share a twin relationship, typically portraying twin characters or being treated as twins within a given context.
-
E.
featuresDetectiveDuo
Indicates that the subject involves or centers around a pair of detectives working together as a team.
- 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_69f07cb3adb48190a9e0e169cd026634 |
completed | April 28, 2026, 9:24 a.m. |
| NER | Named-entity recognition | batch_69ff1f3f94fc819095955299f50ab4ce |
completed | May 9, 2026, 11:49 a.m. |
| PD | Predicate disambiguation | batch_69ff1ea47748819082f63d9b9d9c3e65 |
completed | May 9, 2026, 11:46 a.m. |
| PDg | Predicate description generation | batch_69ff1f3ee3588190a857d1504c93be8b |
completed | May 9, 2026, 11:49 a.m. |
Created at: April 28, 2026, 11:36 a.m.