Triple
T15432828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Value-Creating Society |
E369680
|
entity |
| Predicate | languageOfRendering |
P48899
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Value-Creating Society, languageOfRendering, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfRendering Context triple: [Value-Creating Society, languageOfRendering, English]
-
A.
languageSpecifies
Indicates that one entity defines or constrains the syntax, semantics, or usage rules that govern how another language or linguistic system is expressed or interpreted.
-
B.
languageOfProduct
chosen
Indicates the language in which a product is written, labeled, presented, or otherwise made available.
-
C.
languageOfPrimaryOutput
Indicates the language in which the primary output or main result of an entity (such as a work, process, or system) is expressed.
-
D.
contentLanguage
Indicates the language in which the content is expressed or intended to be understood.
-
E.
languageCategory
Indicates the classification relationship where a language is assigned to a particular linguistic or functional category.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03eda01cc8190843e23b260b8503c |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded27f45548190a6d2b1b85cb47444 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:21 a.m.