Triple
T2662969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lingala |
E54766
|
entity |
| Predicate | writingStandardized |
P30135
|
FINISHED |
| Object | 20th century |
—
|
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: 20th century | Statement: [Lingala, writingStandardized, 20th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: writingStandardized Context triple: [Lingala, writingStandardized, 20th century]
-
A.
writingSystemStandardized
chosen
Indicates that a writing system has been formally codified and regulated according to an accepted standard or set of rules.
-
B.
standardizedFor
Indicates that something has been adjusted or converted to conform to a common standard, format, or reference so it can be consistently compared or used.
-
C.
scriptStandardizationCenter
Indicates a relationship where an entity serves as a center or authority responsible for standardizing a writing system or script.
-
D.
writtenForm
Indicates that one entity is the textual or orthographic representation (spelling or written version) of another entity.
-
E.
standardizedIn
Indicates that something has been formally defined, regulated, or made uniform within a particular standard, framework, or jurisdiction.
- 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd96b9f1c8190a8a9460ca88a9aaf |
completed | March 7, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69abd81768748190bd965f367cf6ef37 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.