Triple
T3096978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angra do Heroísmo |
E64618
|
entity |
| Predicate | hasParish |
P35
|
FINISHED |
| Object |
São Bento
São Bento is a civil parish within the municipality of Angra do Heroísmo on Terceira Island in Portugal’s Azores archipelago.
|
E327501
|
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: São Bento | Statement: [Angra do Heroísmo, hasParish, São Bento]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: São Bento Context triple: [Angra do Heroísmo, hasParish, São Bento]
-
A.
San-São
San-São is the traditional Brazilian football derby between São Paulo FC and Santos FC, known for its historic rivalries and memorable matches.
-
B.
Santos-o-Velho
Santos-o-Velho is a historic riverside neighborhood in Lisbon, Portugal, known for its old convents, palaces, and vibrant nightlife along the Tagus.
-
C.
Sabrosa
Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
-
D.
Santa Cruz do Sul
Santa Cruz do Sul is a city in southern Brazil known for its strong German-Brazilian cultural heritage, architecture, and traditions.
-
E.
Santo Antônio
Santo Antônio is a historic central neighborhood of Recife, Brazil, known for its colonial architecture, commercial activity, and cultural landmarks.
- 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: São Bento Triple: [Angra do Heroísmo, hasParish, São Bento]
Generated description
São Bento is a civil parish within the municipality of Angra do Heroísmo on Terceira Island in Portugal’s Azores archipelago.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: São Bento Target entity description: São Bento is a civil parish within the municipality of Angra do Heroísmo on Terceira Island in Portugal’s Azores archipelago.
-
A.
San-São
San-São is the traditional Brazilian football derby between São Paulo FC and Santos FC, known for its historic rivalries and memorable matches.
-
B.
Santos-o-Velho
Santos-o-Velho is a historic riverside neighborhood in Lisbon, Portugal, known for its old convents, palaces, and vibrant nightlife along the Tagus.
-
C.
Sabrosa
Sabrosa is a small municipality in Portugal’s Douro region, historically notable as the birthplace of explorer Ferdinand Magellan.
-
D.
Santa Cruz do Sul
Santa Cruz do Sul is a city in southern Brazil known for its strong German-Brazilian cultural heritage, architecture, and traditions.
-
E.
Santo Antônio
Santo Antônio is a historic central neighborhood of Recife, Brazil, known for its colonial architecture, commercial activity, and cultural landmarks.
- 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_69ad857dc98481909e585dc3372e3ed5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada23cbe3c8190b7ec5cfd464a1ca8 |
completed | March 8, 2026, 4:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2037483fc8190b8343faa58fb9893 |
completed | March 12, 2026, 12:06 a.m. |
| NEDg | Description generation | batch_69b204a8c5348190a2cb102b08fd6fa5 |
completed | March 12, 2026, 12:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b205bdf5c881908bc6ef7c3c30df65 |
completed | March 12, 2026, 12:15 a.m. |
Created at: March 8, 2026, 3:03 p.m.