Triple
T243557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United First Parish Church, Quincy, Massachusetts |
E4985
|
entity |
| Predicate | hasPortico |
P9740
|
FINISHED |
| Object | classical portico with columns |
—
|
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: classical portico with columns | Statement: [United First Parish Church, Quincy, Massachusetts, hasPortico, classical portico with columns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPortico Context triple: [United First Parish Church, Quincy, Massachusetts, hasPortico, classical portico with columns]
-
A.
hasPortCity
Indicates that a place or region possesses or is associated with a city that functions as its port.
-
B.
hasEntrance
Indicates that one entity possesses or provides an entry point or access way to another entity or space.
-
C.
hasHarbor
Indicates that a place possesses or contains a harbor for docking or sheltering vessels.
-
D.
hasEntranceOn
Indicates that one entity’s entrance or access point is located on or faces a specified side, boundary, or feature of another entity.
-
E.
homePort
Indicates that a vessel or mobile entity is based at, registered to, or primarily operates from a particular port or harbor.
- 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_69a257c3d0708190b0871c4269d273e6 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25dcd2b208190855d5d8d70a3acfc |
completed | Feb. 28, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69a25b62839c8190824064fe5da6a92a |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25dcba5148190ab80fd14c7cf4bb4 |
completed | Feb. 28, 2026, 3:15 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.