Triple
T34780328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington, D.C. Metro station (fictionalized) |
E1002638
|
entity |
| Predicate | transportModeDepicted |
P44050
|
FINISHED |
| Object | rapid transit |
—
|
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: rapid transit | Statement: [Washington, D.C. Metro station (fictionalized), transportModeDepicted, rapid transit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportModeDepicted Context triple: [Washington, D.C. Metro station (fictionalized), transportModeDepicted, rapid transit]
-
A.
transportModePresent
Indicates that a particular mode of transportation is involved or available in the described context or event.
-
B.
transportPattern
Indicates a recurring or characteristic way in which transportation is carried out between entities, such as typical routes, modes, or schedules.
-
C.
transportModeTo
Indicates the means or mode of transportation used to travel to a specified destination.
-
D.
transportType
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
-
E.
transportModeFamily
chosen
Indicates the general category or family of transportation mode to which a specific transport mode belongs (e.g., road, rail, air, water).
- 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_69f76db30a108190bb57ca95b873e5bb |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69ff2eb19ad88190915fbbe08e8bc84e |
completed | May 9, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69ff2db5dd608190b7b7ba95f19c276c |
completed | May 9, 2026, 12:51 p.m. |
Created at: May 3, 2026, 3:59 p.m.