Triple
T22995809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metrô do Recife |
E572186
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
Metrorec
Metrorec is the urban rail and metro system serving the metropolitan region of Recife, Brazil.
|
E1565249
|
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: Metrorec | Statement: [Metrô do Recife, shortName, Metrorec]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Metrorec Context triple: [Metrô do Recife, shortName, Metrorec]
-
A.
Metrorex
Metrorex is the state-owned company responsible for operating and managing the Bucharest Metro system in Romania.
-
B.
Metro
"Metro" is a Russian disaster thriller film featuring Svetlana Khodchenkova in a prominent role, centered on a catastrophic flood in the Moscow subway system.
-
C.
Metro
Metro is the public transport brand used for bus and rail services across West Yorkshire, England.
-
D.
Metro
Metro is the local news section of The Seattle Times that focuses on regional and community coverage in and around the Seattle area.
-
E.
Metro
Metro is a public transport brand operated under Translink, providing urban bus and related transit services.
- 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: Metrorec Triple: [Metrô do Recife, shortName, Metrorec]
Generated description
Metrorec is the urban rail and metro system serving the metropolitan region of Recife, Brazil.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Metrorec Target entity description: Metrorec is the urban rail and metro system serving the metropolitan region of Recife, Brazil.
-
A.
Metrorex
Metrorex is the state-owned company responsible for operating and managing the Bucharest Metro system in Romania.
-
B.
Metro
"Metro" is a Russian disaster thriller film featuring Svetlana Khodchenkova in a prominent role, centered on a catastrophic flood in the Moscow subway system.
-
C.
Metro
Metro is the public transport brand used for bus and rail services across West Yorkshire, England.
-
D.
Metro
Metro is the local news section of The Seattle Times that focuses on regional and community coverage in and around the Seattle area.
-
E.
Metro
Metro is a public transport brand operated under Translink, providing urban bus and related transit services.
- 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_69e245b535808190adef8a9df3c584db |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182f3186c81909e0d5177029a72ae |
completed | April 29, 2026, 4:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bd37cd30c8190ae2fa99f18b59b94 |
completed | May 19, 2026, 3:05 a.m. |
| NEDg | Description generation | batch_6a0bd43af7948190886a30522f3b6c8a |
completed | May 19, 2026, 3:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0bd503b1588190979b9895327a3475 |
completed | May 19, 2026, 3:12 a.m. |
Created at: April 17, 2026, 3:50 p.m.