Triple
T6545634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antonio Maceo International Airport |
E150999
|
entity |
| Predicate | IATAcode |
P418
|
FINISHED |
| Object |
SCU
SCU is the IATA airport code for Antonio Maceo International Airport serving Santiago de Cuba, Cuba.
|
E604412
|
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: SCU | Statement: [Antonio Maceo International Airport, IATAcode, SCU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SCU Context triple: [Antonio Maceo International Airport, IATAcode, SCU]
-
A.
SCS
SCS is Carnegie Mellon University's renowned School of Computer Science, recognized globally for pioneering research and education in computing and related fields.
-
B.
SCB
SCB was a 19th-century Swiss railway company that played a key role in developing the country’s early rail network.
-
C.
SPU
SPU is a private Christian liberal arts university located in Seattle, Washington.
-
D.
HCU
HCU is a leading Indian public research university located in Hyderabad, known for its strong postgraduate programs and emphasis on interdisciplinary studies.
-
E.
UCA
UCA is the Unicode Collation Algorithm, a Unicode standard that defines a language-independent method for ordering and comparing Unicode text.
- 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: SCU Triple: [Antonio Maceo International Airport, IATAcode, SCU]
Generated description
SCU is the IATA airport code for Antonio Maceo International Airport serving Santiago de Cuba, Cuba.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SCU Target entity description: SCU is the IATA airport code for Antonio Maceo International Airport serving Santiago de Cuba, Cuba.
-
A.
SCS
SCS is Carnegie Mellon University's renowned School of Computer Science, recognized globally for pioneering research and education in computing and related fields.
-
B.
SCB
SCB was a 19th-century Swiss railway company that played a key role in developing the country’s early rail network.
-
C.
SPU
SPU is a private Christian liberal arts university located in Seattle, Washington.
-
D.
HCU
HCU is a leading Indian public research university located in Hyderabad, known for its strong postgraduate programs and emphasis on interdisciplinary studies.
-
E.
UCA
UCA is a Jesuit-run Central American University in Managua, Nicaragua, known for its strong emphasis on social justice, human rights, and critical scholarship.
- 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_69c687f3fd60819083bfa583e5bcfa71 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6adee47cc8190830dbc1228b788ee |
completed | March 27, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d54814848190bc397d9b81abc042 |
completed | March 27, 2026, 7:06 p.m. |
| NEDg | Description generation | batch_69c6d67574cc8190acf20c1a598c32ee |
completed | March 27, 2026, 7:11 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6d83b53e48190881a3e1e8fa8b168 |
completed | March 27, 2026, 7:19 p.m. |
Created at: March 27, 2026, 1:50 p.m.