Triple
T12229857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central MTR station |
E291444
|
entity |
| Predicate | hasCode |
P9567
|
FINISHED |
| Object |
CEN
CEN is the station code for Hong Kong’s Central MTR station, a major interchange hub on the city’s rapid transit network.
|
E969231
|
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: CEN | Statement: [Central MTR station, hasCode, CEN]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CEN Context triple: [Central MTR station, hasCode, CEN]
-
A.
CEN
CEN (European Committee for Standardization) is a major European standards organization that develops and maintains voluntary technical standards to support trade, safety, and interoperability across Europe.
-
B.
CEN-SAD
CEN-SAD (Community of Sahel-Saharan States) is a regional economic community in Africa focused on promoting economic integration and cooperation among its mainly Sahel and Sahara region member states.
-
C.
Cen
Cen is the standard astronomical abbreviation for Centaurus, a prominent constellation in the southern sky.
-
D.
LCEN
LCEN is the ICAO airport code for Ercan International Airport, the main air gateway to Northern Cyprus.
-
E.
CNE
CNE is Ecuador’s National Electoral Council, the independent public authority responsible for organizing and overseeing the country’s electoral processes and guaranteeing the transparency of elections.
- 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: CEN Triple: [Central MTR station, hasCode, CEN]
Generated description
CEN is the station code for Hong Kong’s Central MTR station, a major interchange hub on the city’s rapid transit network.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CEN Target entity description: CEN is the station code for Hong Kong’s Central MTR station, a major interchange hub on the city’s rapid transit network.
-
A.
CEN
CEN (European Committee for Standardization) is a major European standards organization that develops and maintains voluntary technical standards to support trade, safety, and interoperability across Europe.
-
B.
CEN-SAD
CEN-SAD (Community of Sahel-Saharan States) is a regional economic community in Africa focused on promoting economic integration and cooperation among its mainly Sahel and Sahara region member states.
-
C.
Cen
Cen is the standard astronomical abbreviation for Centaurus, a prominent constellation in the southern sky.
-
D.
LCEN
LCEN is the ICAO airport code for Ercan International Airport, the main air gateway to Northern Cyprus.
-
E.
CNE
CNE is Chile’s National Energy Commission, the government body responsible for designing, coordinating, and regulating the country’s energy policy and markets.
- 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91ca34fe88190900c8791c70948b7 |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60aad2d488190ba36588e3376ca1a |
completed | May 2, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69f60bdca250819090b4b4cc84d343f4 |
completed | May 2, 2026, 2:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f60cd1668881908f43d895fcfba0aa |
completed | May 2, 2026, 2:40 p.m. |
Created at: April 8, 2026, 9:51 p.m.