Triple
T25006194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Knightsbridge |
E625846
|
entity |
| Predicate | hasPunOn |
P36401
|
FINISHED |
| Object | Knightsbridge (real London district) |
—
|
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: Knightsbridge (real London district) | Statement: [Knightsbridge, hasPunOn, Knightsbridge (real London district)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPunOn Context triple: [Knightsbridge, hasPunOn, Knightsbridge (real London district)]
-
A.
hasTitlePun
chosen
Indicates that an entity’s title involves a pun or wordplay, typically combining multiple meanings or sounds for humorous or clever effect.
-
B.
hasPakad
Indicates that one entity is holding, gripping, or seizing another entity.
-
C.
hasPar
Indicates a relationship where one entity has another entity as its parent.
-
D.
hasHumorType
Indicates that an entity possesses or is characterized by a particular style, category, or type of humor.
-
E.
hasPronaos
Indicates that a structure includes or is characterized by a pronaos, i.e., a front porch or vestibule area preceding the main interior space.
- 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_69e2ff26c50481908bc82e799c9e6587 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f464b4c9b0819085daa00c7c3b8b76 |
completed | May 1, 2026, 8:30 a.m. |
| PD | Predicate disambiguation | batch_69f45cfb53f4819099bba48c5057e787 |
completed | May 1, 2026, 7:57 a.m. |
Created at: April 18, 2026, 6:05 a.m.