Triple
T22981491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Castle |
E571475
|
entity |
| Predicate | basedOnPun |
P18159
|
FINISHED |
| Object | changed surname from Schloss (German for castle) to Castle |
—
|
LITERAL FINISHED |
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: changed surname from Schloss (German for castle) to Castle | Statement: [William Castle, basedOnPun, changed surname from Schloss (German for castle) to Castle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnPun Context triple: [William Castle, basedOnPun, changed surname from Schloss (German for castle) to Castle]
-
A.
namePunOn
chosen
Indicates that one entity’s name is a play on, parody of, or humorous variation of another entity’s name.
-
B.
usedForHumor
Indicates that something is employed with the intention of being funny, amusing, or comical.
-
C.
hasTitlePun
Indicates that an entity’s title involves a pun or wordplay, typically combining multiple meanings or sounds for humorous or clever effect.
-
D.
punchlineStructure
Indicates the structural role or pattern a punchline follows within a joke or humorous setup.
-
E.
usesDoubleEntendre
Indicates that one entity employs language or expressions with a double meaning, often to convey a hidden or suggestive message alongside a literal one.
- 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_69e245b3c50481908bb3741ec9f40862 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1829589548190863619aebcae026c |
completed | April 29, 2026, 4:01 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:49 p.m.