Triple
T8784185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Remembering |
E209003
|
entity |
| Predicate | hasTextLanguage |
P45585
|
FINISHED |
| Object | Chinese |
—
|
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: Chinese | Statement: [Remembering, hasTextLanguage, Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTextLanguage Context triple: [Remembering, hasTextLanguage, Chinese]
-
A.
hasText
Indicates that an entity is associated with or contains a specific piece of textual content.
-
B.
hasLanguageType
chosen
Indicates that an entity is associated with a particular type or category of language (e.g., spoken, written, programming, sign).
-
C.
hasTextualCharacter
Indicates that something possesses or exhibits the qualities of written or printed text, such as letters, symbols, or characters.
-
D.
hasSignificantLanguage
Indicates that an entity possesses a language that plays an important or primary role in its communication, identity, or functioning.
-
E.
hasLanguageCharacter
Indicates that an entity uses, contains, or is associated with a specific written or symbolic character from a language.
- 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_69ca836168108190bb43d3dc235c1f55 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f7441e8819081ea0ae7bc2afde7 |
completed | March 31, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1aff3881908be6a9cbc9f50461 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:42 p.m.