Triple
T14800805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argobba |
E347903
|
entity |
| Predicate | hasVSOOrderVariant |
P115768
|
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: [Argobba, hasVSOOrderVariant, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVSOOrderVariant Context triple: [Argobba, hasVSOOrderVariant, yes]
-
A.
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.
-
B.
hasVariantsIn
Indicates that an entity exists in multiple alternative forms or versions within a specified context or set.
-
C.
hasSVOAlternativeOrder
Indicates that there exists an alternative Subject–Verb–Object word order for expressing the same proposition or relation.
-
D.
hasVariant
Indicates that one entity exists as an alternative form, version, or variation of another entity.
-
E.
hasVariantSeries
Indicates a relationship where one entity is a variant or alternative series derived from or associated with another series.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decd62c36c81909c2993dc7d1a79ea |
completed | April 14, 2026, 11:27 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:31 a.m.