Triple
T2435782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennsylvania German |
E52955
|
entity |
| Predicate | hasV2WordOrder |
P39299
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Pennsylvania German, hasV2WordOrder, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasV2WordOrder Context triple: [Pennsylvania German, hasV2WordOrder, yes]
-
A.
hasBasicWordOrder
Indicates the typical sequence in which core sentence elements (such as subject, verb, and object) are ordered in a language.
-
B.
hasSecondWordOfExpandedForm
Indicates that the second word in the fully expanded (non-abbreviated) form of one entity is related to or associated with another entity.
-
C.
hasTwoWordForm
Indicates that an entity is represented or expressed using a form consisting of exactly two words.
-
D.
hasSVOOrder
Indicates that a language or construction follows a basic word order where the subject comes first, followed by the verb, and then the object.
-
E.
hasTextOrder
Indicates that there is a specified sequence or ordering of text elements relative to one 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_69ab4959bcc0819083246f9fb10439e3 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcebf7cac8190889e6890d72c256c |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5ac11b081908ce6a506e81a742a |
completed | March 7, 2026, 6:29 a.m. |
| PDg | Predicate description generation | batch_69abcebe7dd08190b197a2a0e78787e3 |
completed | March 7, 2026, 7:07 a.m. |
Created at: March 6, 2026, 9:43 p.m.