Triple
T19839558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Antonio International Airport |
E476688
|
entity |
| Predicate | runway |
P1654
|
FINISHED |
| Object |
13R/31L
13R/31L is one of the primary runways at San Antonio International Airport, used for handling a significant portion of the airport’s takeoff and landing traffic.
|
E1399269
|
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: 13R/31L | Statement: [San Antonio International Airport, runway, 13R/31L]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 13R/31L Context triple: [San Antonio International Airport, runway, 13R/31L]
-
A.
13R/31L
13R/31L is a major runway at Dallas/Fort Worth International Airport used for handling high volumes of commercial air traffic.
-
B.
13L/31R
13L/31R is a primary paved runway at San Antonio International Airport used for commercial and general aviation takeoffs and landings.
-
C.
15R/33L
15R/33L is a primary north–south runway at George Bush Intercontinental Airport in Houston, Texas, used for both arrivals and departures of commercial air traffic.
-
D.
12R/30L
12R/30L is a primary paved runway at St. Louis Lambert International Airport used for aircraft takeoffs and landings.
-
E.
R13
R13 is a regional commuter rail line in Catalonia, Spain, operated as part of the Rodalies de Catalunya network.
- 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: 13R/31L Triple: [San Antonio International Airport, runway, 13R/31L]
Generated description
13R/31L is one of the primary runways at San Antonio International Airport, used for handling a significant portion of the airport’s takeoff and landing traffic.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: 13R/31L Target entity description: 13R/31L is one of the primary runways at San Antonio International Airport, used for handling a significant portion of the airport’s takeoff and landing traffic.
-
A.
13R/31L
13R/31L is a major runway at Dallas/Fort Worth International Airport used for handling high volumes of commercial air traffic.
-
B.
13L/31R
13L/31R is a primary paved runway at San Antonio International Airport used for commercial and general aviation takeoffs and landings.
-
C.
15R/33L
15R/33L is a primary north–south runway at George Bush Intercontinental Airport in Houston, Texas, used for both arrivals and departures of commercial air traffic.
-
D.
12R/30L
12R/30L is a primary paved runway at St. Louis Lambert International Airport used for aircraft takeoffs and landings.
-
E.
R13
R13 is a regional commuter rail line in Catalonia, Spain, operated as part of the Rodalies de Catalunya network.
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65804be608190b49e110c3bf381bc |
completed | April 20, 2026, 4:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07dbb8f640819094226b0924bb362c |
completed | May 16, 2026, 2:51 a.m. |
| NEDg | Description generation | batch_6a07dc43a2fc8190991ae7acbe085876 |
completed | May 16, 2026, 2:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07dce4d44481909bc79b8e616ae743 |
completed | May 16, 2026, 2:56 a.m. |
Created at: April 10, 2026, 1:50 p.m.