Triple
T22358933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calvià |
E552727
|
entity |
| Predicate | hasResort |
P4287
|
FINISHED |
| Object |
Peguera
Peguera is a popular beach resort town on the southwest coast of Mallorca, Spain, known for its sandy bays and tourist-friendly promenade.
|
E1532376
|
NE FINISHED |
How this triple was built (4 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: Peguera | Statement: [Calvià, hasResort, Peguera]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peguera Context triple: [Calvià, hasResort, Peguera]
-
A.
Jane T. Castro
Jane T. Castro is a Filipino politician who serves as the elected representative of the municipality of Dumalag.
-
B.
Laura Solon
Laura Solon is a British comedian, writer, and actress known for her award-winning radio and sketch comedy work as well as screenwriting for film and television.
-
C.
Sandy Lopez
Sandy Lopez is a fictional nurse and love interest of Dr. Kerry Weaver on the long-running medical drama television series "ER."
-
D.
Cynthia Villar
Cynthia Villar is a Filipino politician and businesswoman who has served as a senator of the Philippines and is known for her work on housing, entrepreneurship, and social welfare programs.
-
E.
Maria LaGuerta
Maria LaGuerta is a high-ranking and politically savvy Miami Metro Police Department lieutenant in the television series "Dexter."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Peguera Triple: [Calvià, hasResort, Peguera]
Generated description
Peguera is a popular beach resort town on the southwest coast of Mallorca, Spain, known for its sandy bays and tourist-friendly promenade.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Peguera Target entity description: Peguera is a popular beach resort town on the southwest coast of Mallorca, Spain, known for its sandy bays and tourist-friendly promenade.
-
A.
Jane T. Castro
Jane T. Castro is a Filipino politician who serves as the elected representative of the municipality of Dumalag.
-
B.
Laura Solon
Laura Solon is a British comedian, writer, and actress known for her award-winning radio and sketch comedy work as well as screenwriting for film and television.
-
C.
Sandy Lopez
Sandy Lopez is a fictional nurse and love interest of Dr. Kerry Weaver on the long-running medical drama television series "ER."
-
D.
Cynthia Villar
Cynthia Villar is a Filipino politician and businesswoman who has served as a senator of the Philippines and is known for her work on housing, entrepreneurship, and social welfare programs.
-
E.
Maria LaGuerta
Maria LaGuerta is a high-ranking and politically savvy Miami Metro Police Department lieutenant in the television series "Dexter."
- F. None of above. chosen
Provenance (5 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_69e11e4affcc8190ba7c27d29062558d |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157d2b9fc81909e09a1c48664b895 |
completed | April 29, 2026, 12:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ae061d4648190926598d971674630 |
completed | May 18, 2026, 9:48 a.m. |
| NEDg | Description generation | batch_6a0ae17a4d48819094ea2bc413fcb19f |
completed | May 18, 2026, 9:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ae259a6f88190b0ecd726591710b3 |
completed | May 18, 2026, 9:56 a.m. |
Created at: April 16, 2026, 8:44 p.m.