Triple
T4027626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Road |
E83628
|
entity |
| Predicate | travelTimeOnFoot |
P46906
|
FINISHED |
| Object | about 3 months between Sardis and Susa |
—
|
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: about 3 months between Sardis and Susa | Statement: [Royal Road, travelTimeOnFoot, about 3 months between Sardis and Susa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeOnFoot Context triple: [Royal Road, travelTimeOnFoot, about 3 months between Sardis and Susa]
-
A.
nearbyTransit
Indicates that one location has public transportation options situated within a short distance or easy access from it.
-
B.
travelTimeTypical
chosen
Indicates the usual or expected amount of time it takes to travel between two locations under normal conditions.
-
C.
travelTimeCategory
Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
-
D.
pedestrianFriendly
Indicates that an environment, route, or area is designed or suitable for safe, comfortable, and convenient use by pedestrians.
-
E.
hasTrailDistanceToFootbridge
Indicates the length of the trail segment separating a given location or feature from a specified footbridge.
- 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_69aed92e29ac819080f7a98b594fec05 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaeec44881909a6c008eeae204df |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fc78ec819092d4dab88d85a141 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:36 p.m.