Triple
T32818636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Line (Washington Metro) stations |
E839370
|
entity |
| Predicate | servePurpose |
P79
|
FINISHED |
| Object | commuter transport |
—
|
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: commuter transport | Statement: [Red Line (Washington Metro) stations, servePurpose, commuter transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servePurpose Context triple: [Red Line (Washington Metro) stations, servePurpose, commuter transport]
-
A.
servicePurpose
Indicates that one entity serves as the purpose, goal, or intended function for which another entity (typically a service) exists or is provided.
-
B.
purpose
chosen
Indicates that one entity exists, is done, or is used in order to achieve, support, or serve the goal, function, or intended outcome of another entity.
-
C.
traditionalPurpose
Indicates that something serves a role, function, or use that is established by long-standing custom or tradition.
-
D.
meetsForPurpose
Indicates that one entity meets with another specifically to pursue or accomplish a particular purpose or objective.
-
E.
operationalPurpose
Indicates the function, role, or intended use that an entity is designed or configured to perform in an operational context.
- 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_69f3493df9008190a8f5d843dcd77704 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff41645c548190b7cb4e53079b93ef |
completed | May 9, 2026, 2:15 p.m. |
| PD | Predicate disambiguation | batch_69ff410aa33c8190869ba769ac2a93ce |
completed | May 9, 2026, 2:13 p.m. |
Created at: May 1, 2026, 1:15 a.m.