Triple
T1003299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Auto Train |
E21650
|
entity |
| Predicate | travelTimeCategory |
P22194
|
FINISHED |
| Object | overnight journey |
—
|
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: overnight journey | Statement: [Auto Train, travelTimeCategory, overnight journey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeCategory Context triple: [Auto Train, travelTimeCategory, overnight journey]
-
A.
transportReliability
Indicates how consistently and dependably a transport service or system performs as expected over time.
-
B.
nearbyTransit
Indicates that one location has public transportation options situated within a short distance or easy access from it.
-
C.
transportType
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
-
D.
transportationImpact
Indicates how one entity’s transportation-related activities or characteristics affect another entity or the surrounding environment.
-
E.
distanceCategory
Indicates the qualitative classification of how far apart two entities are from each other (e.g., near, medium, far).
- F. None of above. chosen
Provenance (4 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4fe0a548190aee8abf1890e141e |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b1f4f88190822598cfd2a0fd2b |
completed | March 1, 2026, 9:42 p.m. |
| PDg | Predicate description generation | batch_69a4b36064a48190b85c402f32cbadd1 |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:41 p.m.