Triple
T1981307
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mercado de San Juan |
E43030
|
entity |
| Predicate | cuisineServed |
P5786
|
FINISHED |
| Object | Mexican cuisine |
—
|
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: Mexican cuisine | Statement: [Mercado de San Juan, cuisineServed, Mexican cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cuisineServed Context triple: [Mercado de San Juan, cuisineServed, Mexican cuisine]
-
A.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
-
B.
cuisineType
chosen
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
C.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
D.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
-
E.
categoryOfPeopleServed
Indicates the type or group of people that are the primary recipients or beneficiaries of a service or activity.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb96f932881908bebfc4176fda7c0 |
completed | March 7, 2026, 5:36 a.m. |
| PD | Predicate disambiguation | batch_69abb798d288819083132cf14605bd02 |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.