Triple
T9327164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Let's Call the Whole Thing Off |
E224417
|
entity |
| Predicate | usesPronunciationContrast |
P6385
|
FINISHED |
| Object | "tomato" / "tomahto" |
—
|
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: "tomato" / "tomahto" | Statement: [Let's Call the Whole Thing Off, usesPronunciationContrast, "tomato" / "tomahto"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesPronunciationContrast Context triple: [Let's Call the Whole Thing Off, usesPronunciationContrast, "tomato" / "tomahto"]
-
A.
hasPronunciationDifferenceFrom
chosen
Indicates that two linguistic items differ in how they are pronounced.
-
B.
hasPhonemicContrast
Indicates that two or more speech sounds are distinguished in a language by differences that change word meaning.
-
C.
isMorePronouncedIn
Indicates that a particular feature, quality, or effect appears with greater intensity or prominence in one context, entity, or condition than in another.
-
D.
correctPronunciation
Indicates that one entity provides the accurate or standard way to pronounce another entity (such as a word or name).
-
E.
hasExampleWordPronunciation
Indicates that an entity is associated with a specific example of how a word is pronounced.
- 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_69ca8427a0c08190b749831d5ea98f02 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd37aa78648190b786b50402b15569 |
completed | April 1, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69cc7a643924819097f01144734901cf |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:39 p.m.