Triple
T10851427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jiangnan Arsenal |
E256153
|
entity |
| Predicate | languageOfTechnicalMaterials |
P42636
|
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: [Jiangnan Arsenal, languageOfTechnicalMaterials, Chinese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfTechnicalMaterials Context triple: [Jiangnan Arsenal, languageOfTechnicalMaterials, Chinese]
-
A.
languageOfMaterial
Indicates the language in which a given material, resource, or content is expressed or presented.
-
B.
languageOfDocumentation
chosen
Indicates the language in which the documentation for an entity is written or provided.
-
C.
languageOfProduct
Indicates the language in which a product is written, labeled, presented, or otherwise made available.
-
D.
termLanguage
Indicates the language in which a given term is expressed or defined.
-
E.
languagesUsed
Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75117b76c8190b0fb216b1428c3c7 |
completed | April 9, 2026, 7:11 a.m. |
| PD | Predicate disambiguation | batch_69d70d2b51448190bae748ed6c23edde |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.