Triple
T492297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Local Historic Civil Engineering Landmark |
E10215
|
entity |
| Predicate | hasKeyAspect |
P14117
|
FINISHED |
| Object | historical significance |
—
|
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: historical significance | Statement: [Local Historic Civil Engineering Landmark, hasKeyAspect, historical significance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeyAspect Context triple: [Local Historic Civil Engineering Landmark, hasKeyAspect, historical significance]
-
A.
hasAspectSystem
Indicates that an entity possesses or is associated with a particular aspect system, such as a structured set of characteristics, dimensions, or perspectives.
-
B.
hasKeyFigure
Indicates that an entity includes, involves, or is characterized by an important or central person relevant to it.
-
C.
hasKeyWork
Indicates that an entity possesses or is associated with a primary or central work (such as a main publication, artwork, or project) that is especially representative or important.
-
D.
hasKeyIssue
Indicates that an entity is associated with a primary or central problem, concern, or topic of importance.
-
E.
hasKeyType
Indicates that an entity possesses or is associated with a specific category or type of key.
- 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_69a2e847df8481909239ec08ccf1e376 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f0faab4881909f65f172198b5bd2 |
completed | Feb. 28, 2026, 1:43 p.m. |
| PD | Predicate disambiguation | batch_69a2edf7ce008190836fb6ab5ea39375 |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eebb2c908190960a4d0c014304cd |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.