Triple
T10589398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Havaiki |
E249941
|
entity |
| Predicate | oftenSpelled |
P56633
|
FINISHED |
| Object | Hawaiki in English-language scholarship |
—
|
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: Hawaiki in English-language scholarship | Statement: [Havaiki, oftenSpelled, Hawaiki in English-language scholarship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenSpelled Context triple: [Havaiki, oftenSpelled, Hawaiki in English-language scholarship]
-
A.
originalSpelling
Indicates that one entity provides the initial or historically first-used spelling form of another entity’s name or term.
-
B.
hasTypicalSpelling
chosen
Indicates that one form is the standard or commonly accepted spelling of another form.
-
C.
spellingGimmick
Indicates a distinctive or unconventional way of spelling something used for effect or branding rather than standard orthography.
-
D.
effectOnSpelling
Indicates a relationship where one factor influences or alters the way something is spelled.
-
E.
sharesSpellingWith
Indicates that two entities have identical or substantially identical written forms (i.e., they are spelled the same way).
- 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_69d381c9d3d48190a29ee491e1696a0e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d5277a39f08190848f24752cfa4b8f |
completed | April 7, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69d51907b2b881908ab9a8594688ee06 |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:40 p.m.