Triple
T12206544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Accept-Charset |
E290850
|
entity |
| Predicate | canContainToken |
P103781
|
FINISHED |
| Object | charset name |
—
|
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: charset name | Statement: [Accept-Charset, canContainToken, charset name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canContainToken Context triple: [Accept-Charset, canContainToken, charset name]
-
A.
canHold
Indicates that one entity has the capacity or ability to contain, support, or carry another entity.
-
B.
hasContainment
Indicates that one entity spatially or logically encloses, includes, or holds another within its bounds.
-
C.
alsoContains
Indicates that something includes, in addition to its primary contents, another specified element or component.
-
D.
hasContainmentType
Indicates the specific way in which one entity is contained within or enclosed by another.
-
E.
hasVersionToken
Indicates that an entity is associated with a specific version identifier or token that distinguishes one version of it from another.
- F. None of above. chosen
Provenance (4 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d920e312708190b4aede2e21f5f697 |
completed | April 10, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69d91c3d669c81908eea7ad61122d275 |
completed | April 10, 2026, 3:50 p.m. |
| PDg | Predicate description generation | batch_69d920c3dc9881908c396a4ab34f4836 |
completed | April 10, 2026, 4:09 p.m. |
Created at: April 8, 2026, 9:51 p.m.