Triple
T5989751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WMATA 7000-series railcar |
E133314
|
entity |
| Predicate | introducedToService |
P67777
|
FINISHED |
| Object | 2015 |
—
|
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: 2015 | Statement: [WMATA 7000-series railcar, introducedToService, 2015]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedToService Context triple: [WMATA 7000-series railcar, introducedToService, 2015]
-
A.
introducedForServiceWith
Indicates that one entity was presented or brought to the attention of another entity specifically for the purpose of providing a service.
-
B.
introducedTo
Indicates that one entity caused or facilitated a first meeting or formal presentation between another entity and a third party.
-
C.
takenIntoServiceAs
Indicates that one entity has been formally accepted, enrolled, or commissioned to perform service or duty for another entity.
-
D.
hasServiceTo
Indicates that one entity provides, offers, or operates a service for or directed toward another entity.
-
E.
servedByService
Indicates that something is provided, handled, or fulfilled by a particular service.
- 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_69c0087010d081908bb8142342d63330 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04dc76fd481908cc3f327e532a1a6 |
completed | March 22, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69c049de98648190962b14fd341c93da |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04a663a4481908983048c69cba6b6 |
completed | March 22, 2026, 8 p.m. |
Created at: March 22, 2026, 4:05 p.m.