Triple
T21222285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Café del Mar area |
E522998
|
entity |
| Predicate | commonTouristLanguage |
P48682
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [Café del Mar area, commonTouristLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonTouristLanguage Context triple: [Café del Mar area, commonTouristLanguage, English]
-
A.
languageUsedInTourism
chosen
Indicates that a particular language is used for communication and services within tourism activities or contexts.
-
B.
includesLanguagesSpokenAlong
Indicates that something (such as a region, route, or area) encompasses or contains the set of languages spoken along its extent or within its boundaries.
-
C.
languageOfOfficialGuides
Indicates the language in which official guides or instructional materials are provided or published.
-
D.
languagesSpoken
Indicates that an entity is able to communicate using one or more specified languages.
-
E.
languageUsedInLocality
Indicates that a particular language is used or spoken within a specific locality or geographic area.
- 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_69e0b511ed84819099b449b4a111085c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73478d4c48190a241e38719e5bd27 |
completed | April 21, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_69e5f60e1a888190ba75e2e900270a4e |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:43 p.m.