Triple
T18907379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Wade |
E462500
|
entity |
| Predicate | nameComponentOrder |
P28784
|
FINISHED |
| Object | given name followed by family 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: given name followed by family name | Statement: [John Wade, nameComponentOrder, given name followed by family name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameComponentOrder Context triple: [John Wade, nameComponentOrder, given name followed by family name]
-
A.
hasNameOrder
chosen
Indicates the specific sequence or arrangement in which the components of a name (e.g., given name, family name, titles) are ordered.
-
B.
componentOrder
Indicates the relative sequence or arrangement of components within a larger structure or system.
-
C.
nameOrderInChinese
Indicates that the entities are arranged in the order that personal names are written or spoken in Chinese (family name first, given name second).
-
D.
namePosition
Indicates the positional or ordering relationship of a name within a sequence or structured context (e.g., first, last, or specific index).
-
E.
nameElements
Indicates that an entity assigns or specifies the names of multiple elements within a set or structure.
- 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_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c52dcb948190a5b6a783512bf7d6 |
completed | April 20, 2026, 6:18 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e9e6488190ba8df92c8058ed88 |
completed | April 19, 2026, 9:39 a.m. |
Created at: April 10, 2026, 11:58 a.m.