Triple
T36447557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hongoeka Marae |
E897917
|
entity |
| Predicate | hasWharekai |
P185512
|
FINISHED |
| Object | Wharekai (dining hall) |
—
|
NE NERFINISHED |
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: Wharekai (dining hall) | Statement: [Hongoeka Marae, hasWharekai, Wharekai (dining hall)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWharekai Context triple: [Hongoeka Marae, hasWharekai, Wharekai (dining hall)]
-
A.
isMahingaKaiFor
Indicates a relationship where something serves as a traditional food-gathering or resource site for someone or a group (i.e., it functions as mahinga kai for them).
-
B.
haveCuisine
Indicates that an entity (such as a restaurant or place) offers, serves, or is associated with a particular type or style of cuisine.
-
C.
hasWharenui
Indicates a relationship where an entity possesses or is associated with a wharenui (a Māori meeting house).
-
D.
hasFoodOption
Indicates that an entity offers, provides, or includes a particular type of food or dining option.
-
E.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
- 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_69f76e5720b481908f8177ac24a7560b |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be9d07ac8190adf796cbef60daf6 |
completed | May 3, 2026, 9:31 p.m. |
| PD | Predicate disambiguation | batch_69f7bccf05bc8190b61fdb2b2a315811 |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be9b9ab481908328e0e8d8ac73d4 |
completed | May 3, 2026, 9:31 p.m. |
Created at: May 3, 2026, 4:10 p.m.