Triple
T10997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Union Station (Washington, D.C.) |
E223
|
entity |
| Predicate | tracks |
P1291
|
FINISHED |
| Object | 20+ |
—
|
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: 20+ | Statement: [Union Station (Washington, D.C.), tracks, 20+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tracks Context triple: [Union Station (Washington, D.C.), tracks, 20+]
-
A.
trackGauge
Indicates the distance between the inner faces of the rails in a railway track system.
-
B.
follows
Indicates that one entity comes after, moves behind, or acts in accordance with another entity in time, space, or sequence.
-
C.
musicTradition
Indicates a relationship where one entity follows, embodies, or belongs to a particular musical tradition or style associated with another entity.
-
D.
drivesOn
Indicates that an entity uses or travels along a particular route, surface, or roadway as its path of movement.
-
E.
transportation
Indicates the movement of someone or something from one place to another, typically using a vehicle or transit system.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a242cd8fb481909562f114f4ce7700 |
completed | Feb. 28, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69a23fe6b0bc8190bcce9b74f2c5fb08 |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a242cce40481908e5eae0c94313c25 |
completed | Feb. 28, 2026, 1:20 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.