Triple
T19376612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 河 |
E484683
|
entity |
| Predicate | isUsedInEverydayVocabulary |
P11801
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [河, isUsedInEverydayVocabulary, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUsedInEverydayVocabulary Context triple: [河, isUsedInEverydayVocabulary, true]
-
A.
isUsedInPhrase
Indicates that something (such as a word, expression, or symbol) appears as a component within a particular phrase.
-
B.
isFamouslyUsedIn
Indicates that something is widely recognized or well-known for being used in a particular context, work, or situation.
-
C.
isUsedInAbbreviation
Indicates that one entity functions as a shortened or abbreviated form of another entity.
-
D.
widelyUsedIn
chosen
Indicates that something is commonly or extensively utilized within a particular context, domain, or group.
-
E.
usedInSpokenForm
Indicates that something (such as a word, name, or expression) is employed in spoken language or oral communication.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61a5cfbf48190ac60e3ffa6baa263 |
completed | April 20, 2026, 12:21 p.m. |
| PD | Predicate disambiguation | batch_69e4fd54f8e48190956e73dd8969164a |
completed | April 19, 2026, 4:05 p.m. |
Created at: April 10, 2026, 1:35 p.m.