Triple
T7614662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sal (Cape Verde) |
E172331
|
entity |
| Predicate | airportIATAcode |
P418
|
FINISHED |
| Object |
SID
SID is the IATA airport code for Amílcar Cabral International Airport, the main airport on Sal Island in Cape Verde.
|
E675989
|
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: SID | Statement: [Sal (Cape Verde), airportIATAcode, SID]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SID Context triple: [Sal (Cape Verde), airportIATAcode, SID]
-
A.
Si
Si is one of the mischievous Siamese cats from Disney’s animated film "Lady and the Tramp," known for causing trouble with her twin, Am.
-
B.
SI
SI is the abbreviation for Skeptical Inquirer, a magazine devoted to scientific skepticism, critical thinking, and the investigation of extraordinary claims.
-
C.
SI
SI is the globally accepted metric-based system of measurement used in science, industry, and everyday life.
-
D.
SIMID
SIMID (Secure Interactive Media Interface Definition) is a digital advertising standard that defines how interactive video ads communicate and operate within video players across platforms.
-
E.
Sid
Sid is a minor character in Mark Twain's novel "The Adventures of Tom Sawyer," known as Tom's well-behaved, tattletale half-brother who often contrasts Tom's mischievous nature.
- 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: SID Triple: [Sal (Cape Verde), airportIATAcode, SID]
Generated description
SID is the IATA airport code for Amílcar Cabral International Airport, the main airport on Sal Island in Cape Verde.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: SID Target entity description: SID is the IATA airport code for Amílcar Cabral International Airport, the main airport on Sal Island in Cape Verde.
-
A.
Si
Si is one of the mischievous Siamese cats from Disney’s animated film "Lady and the Tramp," known for causing trouble with her twin, Am.
-
B.
SI
SI is the abbreviation for Skeptical Inquirer, a magazine devoted to scientific skepticism, critical thinking, and the investigation of extraordinary claims.
-
C.
SI
SI is the globally accepted metric-based system of measurement used in science, industry, and everyday life.
-
D.
SIMID
SIMID (Secure Interactive Media Interface Definition) is a digital advertising standard that defines how interactive video ads communicate and operate within video players across platforms.
-
E.
Sid
Sid is a supporting character in the film "The Descendants," contributing to the story’s emotional and comedic dynamics around a family coping with loss and change.
- 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_69c6994f50808190ba228764bb422417 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fa4392e881908ed1ab3f64b41600 |
completed | March 27, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8686d16808190bc431c43c0928f6e |
completed | March 28, 2026, 11:46 p.m. |
| NEDg | Description generation | batch_69c8691bf25881909585bb04404f90da |
completed | March 28, 2026, 11:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8698f70a081909633b3b6d7fd45e1 |
completed | March 28, 2026, 11:51 p.m. |
Created at: March 27, 2026, 3:55 p.m.