Triple
T19606752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taba Border Crossing |
E470624
|
entity |
| Predicate | allowsModeOfTravel |
P37966
|
FINISHED |
| Object | pedestrian crossing |
—
|
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: pedestrian crossing | Statement: [Taba Border Crossing, allowsModeOfTravel, pedestrian crossing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allowsModeOfTravel Context triple: [Taba Border Crossing, allowsModeOfTravel, pedestrian crossing]
-
A.
transportModeAccess
chosen
Indicates that one entity has the ability or permission to use, reach, or be served by a particular mode of transportation.
-
B.
appliesToTransportMode
Indicates that a rule, condition, or characteristic is specifically associated with and relevant to a particular mode of transport.
-
C.
usedTransportationMode
Indicates that an entity traveled or moved using a specified mode of transportation.
-
D.
publicTransportAllowed
Indicates that the use of public transportation is permitted or authorized in the given context or for the specified entities.
-
E.
publicTransitMode
Indicates the type of public transportation (e.g., bus, train, subway) used or associated with a given trip or segment.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640c7ed24819091502fe0d5e139bc |
completed | April 20, 2026, 3:05 p.m. |
| PD | Predicate disambiguation | batch_69e514e166dc8190a0f147e0b4c8bbe7 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:43 p.m.