Triple
T17494900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whanganui |
E426030
|
entity |
| Predicate | nameSpellingStandardized |
P127663
|
FINISHED |
| Object | 2015 |
—
|
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: 2015 | Statement: [Whanganui, nameSpellingStandardized, 2015]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameSpellingStandardized Context triple: [Whanganui, nameSpellingStandardized, 2015]
-
A.
nameStyle
Indicates how an entity’s name is formatted or stylistically presented (e.g., capitalization, punctuation, or naming convention).
-
B.
namedAccordingTo
Indicates that one entity is given a name that follows, references, or is derived from another entity or source.
-
C.
transcribedName
Indicates that one entity is a written or phonetic rendering of another entity’s name, typically adapted to a different script, language, or transcription system.
-
D.
nameDistinction
Indicates that two entities are distinguished from one another specifically by differences in their names.
-
E.
writingSystemStandardized
Indicates that a writing system has been formally codified and regulated according to an accepted standard or set of rules.
- 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_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4520dd9508190872a71d3722228e2 |
completed | April 19, 2026, 3:54 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f5fbcc8190a6ea9639bf5650da |
completed | April 18, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69e3bbb37d148190b7f38599c06594ee |
completed | April 18, 2026, 5:13 p.m. |
Created at: April 10, 2026, 5:48 a.m.