Triple
T1670382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MBTA bus route 39 |
E36109
|
entity |
| Predicate | servesInstitutionalArea |
P31588
|
FINISHED |
| Object | hospitals in Longwood Medical Area |
—
|
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: hospitals in Longwood Medical Area | Statement: [MBTA bus route 39, servesInstitutionalArea, hospitals in Longwood Medical Area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesInstitutionalArea Context triple: [MBTA bus route 39, servesInstitutionalArea, hospitals in Longwood Medical Area]
-
A.
servesInstitution
Indicates that one entity provides services or functions in support of a particular institution.
-
B.
regionOfInstitution
Indicates that a specified region is the geographic area in which an institution is located or operates.
-
C.
centralInstitutionOf
Indicates that one institution serves as the primary or main institutional center for another entity, such as an organization, system, or region.
-
D.
involvesInstitution
Indicates that an action, event, or relationship includes or is associated with an institution as a participating party.
-
E.
establishedInstitution
Indicates that an entity founded, created, or formally set up an institution or organization.
- 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_69a8861286808190939afff3ce8ee31e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab272a653481908f48aa1eed5de8a4 |
completed | March 6, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_69aa61b2f6288190b2348ef7d7e4672d |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab271be3f4819091adcd745dec8159 |
completed | March 6, 2026, 7:12 p.m. |
Created at: March 4, 2026, 7:29 p.m.