Triple
T27635583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delmar Loop |
E696459
|
entity |
| Predicate | hasCuisineDiversity |
P88640
|
FINISHED |
| Object | international restaurants |
—
|
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: international restaurants | Statement: [Delmar Loop, hasCuisineDiversity, international restaurants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCuisineDiversity Context triple: [Delmar Loop, hasCuisineDiversity, international restaurants]
-
A.
haveDistinctCulinaryTraditions
Indicates that the related entities possess different and distinguishable culinary practices, cuisines, or food-related customs from one another.
-
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.
hasVarietyOf
chosen
Indicates that an entity possesses or offers multiple different types, forms, or versions of something.
-
D.
hasCuisineRecognition
Indicates that an entity has received formal recognition, awards, or notable acknowledgment specifically for its cuisine.
-
E.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
- 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_69ef5909f3848190805f35b76833e722 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f7465687bc8190a9da44d62b634ed7 |
completed | May 3, 2026, 12:57 p.m. |
| PD | Predicate disambiguation | batch_69f743f4ceb08190a21fe7f4a99b166b |
completed | May 3, 2026, 12:47 p.m. |
Created at: April 27, 2026, 2:23 p.m.