Triple
T20142
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlestown, Massachusetts Bay Colony |
E399
|
entity |
| Predicate | hadDefensiveImportance |
P1090
|
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: [Charlestown, Massachusetts Bay Colony, hadDefensiveImportance, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadDefensiveImportance Context triple: [Charlestown, Massachusetts Bay Colony, hadDefensiveImportance, yes]
-
A.
defender
Indicates a relationship where one entity protects, guards, or supports another entity against threats, attacks, or criticism.
-
B.
historicalStronghold
chosen
Indicates that a location has historically served as a fortified center of power, defense, or control for a group or authority.
-
C.
historicallyPrizedFor
Indicates that something has been especially valued or esteemed for a particular quality, use, or significance in the past.
-
D.
typeOfDefense
Indicates the specific kind or category of defense employed or possessed in a given context.
-
E.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
- 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_69a240778d288190815c0052ebbbcc91 |
completed | Feb. 28, 2026, 1:10 a.m. |
| NER | Named-entity recognition | batch_69a24703cb988190ad2bc181d27829e4 |
completed | Feb. 28, 2026, 1:38 a.m. |
| PD | Predicate disambiguation | batch_69a24650f1f0819081e638fafd18d687 |
completed | Feb. 28, 2026, 1:35 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.