Triple
T17250725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eduardo VII Park |
E418743
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Estufa Quente
Estufa Quente is a historic greenhouse complex in Lisbon, Portugal, known for its lush exotic plant collections and scenic setting within Eduardo VII Park.
|
E1258708
|
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: Estufa Quente | Statement: [Eduardo VII Park, hasPart, Estufa Quente]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Estufa Quente Context triple: [Eduardo VII Park, hasPart, Estufa Quente]
-
A.
Fogão
Fogão is the popular nickname of Brazilian football club Botafogo de Futebol e Regatas, one of Rio de Janeiro’s traditional teams.
-
B.
Roastmaster
Roastmaster is the nickname of comedian Jeffrey Ross, renowned for his sharp, insult-based comedy and frequent appearances at celebrity roasts.
-
C.
Blodgett
Blodgett is a surname of English origin borne by various notable individuals across fields such as politics, business, and the arts.
-
D.
Boiling Pot
Boiling Pot is a turbulent section of the Zambezi River below Victoria Falls, known for its powerful whirlpools and dramatic gorge scenery.
-
E.
Boiling Pot
Boiling Pot is a 2015 American drama film that explores racial tensions and prejudice on a college campus.
- 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: Estufa Quente Triple: [Eduardo VII Park, hasPart, Estufa Quente]
Generated description
Estufa Quente is a historic greenhouse complex in Lisbon, Portugal, known for its lush exotic plant collections and scenic setting within Eduardo VII Park.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Estufa Quente Target entity description: Estufa Quente is a historic greenhouse complex in Lisbon, Portugal, known for its lush exotic plant collections and scenic setting within Eduardo VII Park.
-
A.
Fogão
Fogão is the popular nickname of Brazilian football club Botafogo de Futebol e Regatas, one of Rio de Janeiro’s traditional teams.
-
B.
Roastmaster
Roastmaster is the nickname of comedian Jeffrey Ross, renowned for his sharp, insult-based comedy and frequent appearances at celebrity roasts.
-
C.
Blodgett
Blodgett is a surname of English origin borne by various notable individuals across fields such as politics, business, and the arts.
-
D.
Boiling Pot
Boiling Pot is a turbulent section of the Zambezi River below Victoria Falls, known for its powerful whirlpools and dramatic gorge scenery.
-
E.
Boiling Pot
Boiling Pot is a 2015 American drama film that explores racial tensions and prejudice on a college campus.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e270fc48190a75f3893a5ec059b |
completed | April 19, 2026, 1:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0170f96e548190be92846e072118f9 |
completed | May 11, 2026, 6:02 a.m. |
| NEDg | Description generation | batch_6a01717495208190b415219d15e71fb7 |
completed | May 11, 2026, 6:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01721f5b9081909a8bc817ba0a5986 |
completed | May 11, 2026, 6:07 a.m. |
Created at: April 10, 2026, 5:39 a.m.