Triple
T2345630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bahia |
E45123
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Tricolor de Aço
Tricolor de Aço is the popular nickname of Esporte Clube Bahia, a traditional Brazilian football club known for its three-colored kit and passionate fanbase.
|
E257554
|
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: Tricolor de Aço | Statement: [Bahia, nickname, Tricolor de Aço]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tricolor de Aço Context triple: [Bahia, nickname, Tricolor de Aço]
-
A.
The Iron
The Iron is the English title of Surah Al-Hadid, the 57th chapter of the Qur’an, which emphasizes faith, charity, and the transient nature of worldly life.
-
B.
Ferro
Ferro is an alternative name for El Hierro, the smallest and westernmost of Spain’s Canary Islands in the Atlantic Ocean.
-
C.
Blau
The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
-
D.
Tinte
Tinte is a small village in the Dutch province of South Holland, known for its rural character and annual local festivities.
-
E.
Steelman
Steelman is a surname of English origin borne by various notable individuals, including American economist and presidential advisor John R. Steelman.
- 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: Tricolor de Aço Triple: [Bahia, nickname, Tricolor de Aço]
Generated description
Tricolor de Aço is the popular nickname of Esporte Clube Bahia, a traditional Brazilian football club known for its three-colored kit and passionate fanbase.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tricolor de Aço Target entity description: Tricolor de Aço is the popular nickname of Esporte Clube Bahia, a traditional Brazilian football club known for its three-colored kit and passionate fanbase.
-
A.
The Iron
The Iron is the English title of Surah Al-Hadid, the 57th chapter of the Qur’an, which emphasizes faith, charity, and the transient nature of worldly life.
-
B.
Ferro
Ferro is an alternative name for El Hierro, the smallest and westernmost of Spain’s Canary Islands in the Atlantic Ocean.
-
C.
Blau
The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
-
D.
Tinte
Tinte is a small village in the Dutch province of South Holland, known for its rural character and annual local festivities.
-
E.
Steelman
Steelman is a surname of English origin borne by various notable individuals, including American economist and presidential advisor John R. Steelman.
- 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_69a88917935081909b755dbf38e81024 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abc6c7cb9481909405aeb503f804ae |
completed | March 7, 2026, 6:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae9628059481909c96a7661bc87a73 |
completed | March 9, 2026, 9:43 a.m. |
| NEDg | Description generation | batch_69ae9727a28881909eebc67189dfc856 |
completed | March 9, 2026, 9:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae9795cf048190bc7a01ef86c12138 |
completed | March 9, 2026, 9:49 a.m. |
Created at: March 4, 2026, 7:52 p.m.