Triple
T254571
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Westchester County, New York |
E5408
|
entity |
| Predicate | foundedAsCounty |
P8950
|
FINISHED |
| Object | 1683 |
—
|
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: 1683 | Statement: [Westchester County, New York, foundedAsCounty, 1683]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foundedAsCounty Context triple: [Westchester County, New York, foundedAsCounty, 1683]
-
A.
foundedAs
Indicates the original name or form under which an organization, institution, or entity was first established.
-
B.
foundedOn
Indicates that an entity was established, created, or brought into existence on a specific date or point in time.
-
C.
isFoundedOn
Indicates that one entity is established, created, or based upon another entity as its foundational source or principle.
-
D.
foundedBefore
Indicates that one entity was established or created at an earlier time than the other entity.
-
E.
incorporatedAsTownIn
Indicates that an entity was officially established and given legal status as a town within a specified jurisdiction.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25d548cac819081b1636b2a057c62 |
completed | Feb. 28, 2026, 3:13 a.m. |
| PD | Predicate disambiguation | batch_69a25b694c08819085bb4b256fa7736f |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25c4b773c81908f1017f40b0bfd07 |
completed | Feb. 28, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.