Triple
T6284978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mercado de San Miguel |
E140877
|
entity |
| Predicate | cityAttractionType |
P8077
|
FINISHED |
| Object | gastronomic market |
—
|
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: gastronomic market | Statement: [Mercado de San Miguel, cityAttractionType, gastronomic market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityAttractionType Context triple: [Mercado de San Miguel, cityAttractionType, gastronomic market]
-
A.
attractionType
chosen
Indicates the specific kind or category of attraction that characterizes the relationship between entities.
-
B.
isMajorAttractionFor
Indicates that something serves as a primary or highly significant draw or point of interest for a particular audience, group, or location.
-
C.
touristAttractionIn
Indicates that a place functions as a tourist attraction located within a specified geographic area or entity.
-
D.
hasTouristAttractionRole
Indicates that an entity serves in the capacity or function of a tourist attraction for another entity (such as a place, organization, or area).
-
E.
relatedAttraction
Indicates that one attraction is associated with or connected to another attraction in some relevant 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_69c008cd17c8819082b82d3fbeb68047 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063fc906481908283c6c50a212515 |
completed | March 22, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69c0560a0270819098ad2785b91e8f39 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:26 p.m.