Triple
T20113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlestown, Massachusetts Bay Colony |
E399
|
entity |
| Predicate | foundedInYearApprox |
P1825
|
FINISHED |
| Object | 1628 |
—
|
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: 1628 | Statement: [Charlestown, Massachusetts Bay Colony, foundedInYearApprox, 1628]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foundedInYearApprox Context triple: [Charlestown, Massachusetts Bay Colony, foundedInYearApprox, 1628]
-
A.
foundedOn
Indicates that an entity was established, created, or brought into existence on a specific date or point in time.
-
B.
foundedAfter
Indicates that one entity was founded at a later time than another entity.
-
C.
foundedAs
Indicates the original name or form under which an organization, institution, or entity was first established.
-
D.
foundedFor
Indicates that an entity was established or created specifically to serve, support, or benefit another entity or purpose.
-
E.
wasInventedInYear
Indicates that an entity was created or invented in a specific calendar year.
- 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_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. |
| PDg | Predicate description generation | batch_69a24702d4988190a54a4e578b7c919e |
completed | Feb. 28, 2026, 1:38 a.m. |
Created at: Feb. 28, 2026, 1:14 a.m.