Triple
T1577437
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lanzarote |
E33684
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Tías
Tías is a coastal municipality on the Spanish island of Lanzarote in the Canary Islands, known for the popular tourist resort of Puerto del Carmen.
|
E178572
|
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: Tías | Statement: [Lanzarote, hasMunicipality, Tías]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tías Context triple: [Lanzarote, hasMunicipality, Tías]
-
A.
Teressa
Teressa is a Nicobarese language variety spoken by the indigenous community on Teressa Island in India’s Nicobar archipelago.
-
B.
Rosalinda
Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
-
C.
Hilda
Hilda is the middle name of Margaret Thatcher, the former Prime Minister of the United Kingdom.
-
D.
Teresa
Teresa is the religious name of Mother Teresa, the Catholic nun and missionary renowned for her charitable work with the poor in Kolkata, India.
-
E.
Lucilla
Lucilla was a Roman imperial princess and daughter of Emperor Marcus Aurelius who became Empress as the wife of Lucius Verus and was later implicated in a plot against her brother Commodus.
- 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: Tías Triple: [Lanzarote, hasMunicipality, Tías]
Generated description
Tías is a coastal municipality on the Spanish island of Lanzarote in the Canary Islands, known for the popular tourist resort of Puerto del Carmen.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tías Target entity description: Tías is a coastal municipality on the Spanish island of Lanzarote in the Canary Islands, known for the popular tourist resort of Puerto del Carmen.
-
A.
Teressa
Teressa is a Nicobarese language variety spoken by the indigenous community on Teressa Island in India’s Nicobar archipelago.
-
B.
Rosalinda
Rosalinda is a feminine given name of Spanish and Italian origin, often interpreted to mean "beautiful rose."
-
C.
Hilda
Hilda is the middle name of Margaret Thatcher, the former Prime Minister of the United Kingdom.
-
D.
Teresa
Teresa is the religious name of Mother Teresa, the Catholic nun and missionary renowned for her charitable work with the poor in Kolkata, India.
-
E.
Lucilla
Lucilla was a Roman imperial princess and daughter of Emperor Marcus Aurelius who became Empress as the wife of Lucius Verus and was later implicated in a plot against her brother Commodus.
- 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_69a885f27a4c8190a4622252cdf54c00 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a908d571f081908acec43ff2ef112d |
completed | March 5, 2026, 4:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad402e1cc48190bb69628bc63d6f4c |
completed | March 8, 2026, 9:23 a.m. |
| NEDg | Description generation | batch_69ad40e7db808190a94dd9932ea8d6c4 |
completed | March 8, 2026, 9:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad417c2ff48190af8e62a015b45c6b |
completed | March 8, 2026, 9:29 a.m. |
Created at: March 4, 2026, 7:27 p.m.