Triple
T9629526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boylston |
E232560
|
entity |
| Predicate | hasHistoricStreetcarsDisplayed |
P89352
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [Boylston, hasHistoricStreetcarsDisplayed, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricStreetcarsDisplayed Context triple: [Boylston, hasHistoricStreetcarsDisplayed, Yes]
-
A.
hasStreetcarHistory
Indicates that there is a historical association or past involvement with streetcars or streetcar systems.
-
B.
hasHistoricStreet
Indicates that an entity is associated with or located on a street that has recognized historical significance.
-
C.
hasTramHistory
Indicates that there exists a historical association or record of tram-related activity or infrastructure involving the subject.
-
D.
hasRailroadHistoryWith
Indicates a historical relationship or connection between entities involving railroads, such as shared development, operation, or significant events in railway history.
-
E.
hasStreetcarLoop
Indicates that a location or facility includes a dedicated looped track or route specifically for streetcars to turn around or circulate.
- 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_69ca848793ec8190a93a12383a754dc0 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b00162481908f396f6b6e470d6c |
completed | April 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69ccd5acfa5c8190aaba3cf548723604 |
completed | April 1, 2026, 8:22 a.m. |
| PDg | Predicate description generation | batch_69ccd93fc45c8190a823305e461e581d |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:10 p.m.