Triple
T38682345
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SH 71 Toll (Austin–Bergstrom Expressway) |
E949020
|
entity |
| Predicate | isAirportConnector |
P23780
|
FINISHED |
| Object | yes |
—
|
LITERAL FINISHED |
How this triple was built (2 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: yes | Statement: [SH 71 Toll (Austin–Bergstrom Expressway), isAirportConnector, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isAirportConnector Context triple: [SH 71 Toll (Austin–Bergstrom Expressway), isAirportConnector, yes]
-
A.
connectsWithAirport
chosen
Indicates that there is a direct transportation or operational link established between an entity and an airport.
-
B.
hasAirportAccessTo
Indicates that one location or entity has direct access to another via an airport connection or service.
-
C.
isBorderAirport
Indicates that an airport is located near or on a national or regional border, serving cross-border traffic or border-adjacent areas.
-
D.
hasAirsideConnection
Indicates that there is a direct, secure connection between areas past security (airside) of two locations, allowing passengers to transfer without re-clearing security or immigration.
-
E.
isAirportRailLink
Indicates that a rail service or line provides a direct transportation connection to an airport.
- F. None of above.
Provenance (3 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_69f76efe16148190befd5dd59c3dfeaa |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.