Triple
T11293305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Macca’s |
E267383
|
entity |
| Predicate | usedInSpokenLanguage |
P15075
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Macca’s, usedInSpokenLanguage, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInSpokenLanguage Context triple: [Macca’s, usedInSpokenLanguage, yes]
-
A.
usedInSpokenForm
chosen
Indicates that something (such as a word, name, or expression) is employed in spoken language or oral communication.
-
B.
usedInLanguage
Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
-
C.
isSpokenOn
Indicates that a particular language, phrase, or utterance is used or occurs during a specified time, event, or occasion.
-
D.
isSpokenLanguage
Indicates that a language is used primarily for oral communication by speakers, as opposed to being only written or symbolic.
-
E.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
- 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_69d6aac993a08190a6f36445ebaf9a43 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e98b149481909f432a6b9ef8bfbb |
completed | April 9, 2026, 6:01 p.m. |
| PD | Predicate disambiguation | batch_69d787a6ca2c8190afdc24b61ccd3f8a |
completed | April 9, 2026, 11:04 a.m. |
Created at: April 8, 2026, 9:32 p.m.