Triple
T276512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shawmut |
E5260
|
entity |
| Predicate | stationHouseType |
P1844
|
FINISHED |
| Object | neighborhood station house |
—
|
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: neighborhood station house | Statement: [Shawmut, stationHouseType, neighborhood station house]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stationHouseType Context triple: [Shawmut, stationHouseType, neighborhood station house]
-
A.
buildingType
chosen
Indicates the specific category or function that characterizes what kind of building something is.
-
B.
towerType
Indicates the specific kind or classification of a tower that an entity is associated with or represents.
-
C.
architectureType
Indicates the specific style or category of architecture that characterizes or defines an entity.
-
D.
hasStationBuilding
Indicates that a station is associated with or includes a station building as part of its facilities.
-
E.
policePrecinct
Indicates that a specified location, building, or area functions as or is designated as a police precinct.
- 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_69a257e6c8788190987dfe705ca2912a |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25dec53ac8190912f3d79576131fa |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b7480e881909399beccfc7ffb81 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:59 a.m.