Triple
T1301668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Street Station |
E27776
|
entity |
| Predicate | hasRestorationFocus |
P26782
|
FINISHED |
| Object | historic preservation |
—
|
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: historic preservation | Statement: [King Street Station, hasRestorationFocus, historic preservation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRestorationFocus Context triple: [King Street Station, hasRestorationFocus, historic preservation]
-
A.
hasRestoration
Indicates that an entity has undergone, is undergoing, or is associated with a process of repair, renewal, or restoration.
-
B.
hasPrimaryFocus
Indicates that something is the main subject, concern, or area of attention for an entity or activity.
-
C.
hasCollectionFocus
Indicates that something is primarily concerned with, centered on, or directed toward a particular collection or set of items.
-
D.
hasRestorationActivities
Indicates that an entity carries out, is involved in, or is associated with actions aimed at restoring or rehabilitating another entity or resource.
-
E.
mayProvideFocus
Indicates that one entity can potentially direct attention, emphasis, or concentration toward another entity or aspect.
- 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_69a496d6682881909ba658f1c1e0e2b0 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c1145c2481908adf22dfd6ce349b |
completed | March 1, 2026, 10:43 p.m. |
| PD | Predicate disambiguation | batch_69a4bee8544c8190874efd9bae9bccf9 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4bf60545c8190901ccfb2cb7c4b41 |
completed | March 1, 2026, 10:36 p.m. |
Created at: March 1, 2026, 7:51 p.m.