Triple
T890707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stadium of Delphi |
E19230
|
entity |
| Predicate | hasTrackLanes |
P20753
|
FINISHED |
| Object | single straight track |
—
|
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: single straight track | Statement: [Stadium of Delphi, hasTrackLanes, single straight track]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrackLanes Context triple: [Stadium of Delphi, hasTrackLanes, single straight track]
-
A.
hasLanes
Indicates that an entity, such as a road or pathway, is divided into one or more distinct lanes for traffic or movement.
-
B.
laneCount
Indicates the number of parallel lanes associated with a given road or roadway segment.
-
C.
hasExpressLanes
Indicates that a roadway or transportation facility includes designated express lanes for faster or prioritized travel.
-
D.
numberOfRailwayTracks
Indicates the quantity of railway tracks associated with or present at a given entity or location.
-
E.
hasTrack
Indicates that one entity possesses, includes, or is associated with a specific track (such as a path, course, or recorded item).
- 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_69a4939d37188190848be3d426ebc9ae |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad0086a081908c47c285896a1f3c |
completed | March 1, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69a4aa9372e88190b5a9db4afdc045c6 |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab4a38ec8190915916d80299ab55 |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:39 p.m.