Triple
T142267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Station |
E2878
|
entity |
| Predicate | hasServiceTo |
P6787
|
FINISHED |
| Object | northern suburbs of Boston |
—
|
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: northern suburbs of Boston | Statement: [North Station, hasServiceTo, northern suburbs of Boston]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasServiceTo Context triple: [North Station, hasServiceTo, northern suburbs of Boston]
-
A.
hasServiceType
Indicates that an entity is associated with or categorized by a particular type of service.
-
B.
hasFormerService
Indicates that an entity previously provided a service to another entity but no longer does so.
-
C.
hasServant
Indicates that one entity has another entity serving it in a subordinate or attendant role.
-
D.
servedByService
Indicates that something is provided, handled, or fulfilled by a particular service.
-
E.
hasUserService
Indicates that an entity is associated with or utilizes a particular user-related 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a2580ca15481909fa3e87d804a1b23 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a2565559ac81909e0c4e095a7dfa27 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2580b00988190868ee24c0289cf70 |
completed | Feb. 28, 2026, 2:50 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.