Triple
T38536160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul O’Grady: For the Love of Dogs |
E923503
|
entity |
| Predicate | hasSpinOffOrSpecials |
P16447
|
FINISHED |
| Object | Paul O’Grady: For the Love of Dogs at Christmas |
—
|
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: Paul O’Grady: For the Love of Dogs at Christmas | Statement: [Paul O’Grady: For the Love of Dogs, hasSpinOffOrSpecials, Paul O’Grady: For the Love of Dogs at Christmas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpinOffOrSpecials Context triple: [Paul O’Grady: For the Love of Dogs, hasSpinOffOrSpecials, Paul O’Grady: For the Love of Dogs at Christmas]
-
A.
hasSpinOff
Indicates that one entity is a derivative or spin-off product, work, or organization that originated from another entity.
-
B.
hasSpinOffLabel
Indicates that one entity serves as a spin-off label or subsidiary label that originated from another label entity.
-
C.
hasSpinOffDevelopment
Indicates that one entity has led to or produced a derivative or spin-off development based on it.
-
D.
hasSpinOffPlatform
Indicates that one entity has given rise to or is associated with a derivative or spin-off platform based on the original.
-
E.
includesSpecialEpisodes
chosen
Indicates that the subject collection or series contains one or more special, non-regular episodes.
- F. None of above.
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_69f76ea8f6348190a5c03fb6292bbee3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff27b125948190aced0fe0189fd39a |
completed | May 9, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69ff26c30a0481909ef6a54ded851e42 |
completed | May 9, 2026, 12:21 p.m. |
Created at: May 3, 2026, 4:32 p.m.