Triple
T841141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huntington Avenue Grounds |
E18178
|
entity |
| Predicate | eraCategory |
P87
|
FINISHED |
| Object | 1900s sports venues in the United States |
—
|
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: 1900s sports venues in the United States | Statement: [Huntington Avenue Grounds, eraCategory, 1900s sports venues in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eraCategory Context triple: [Huntington Avenue Grounds, eraCategory, 1900s sports venues in the United States]
-
A.
category
chosen
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
B.
era
Indicates that something existed, occurred, or was valid during a specified historical or temporal period.
-
C.
genre
Indicates the artistic or thematic category to which a work (such as a book, film, or song) belongs.
-
D.
notableCategory
Indicates that an entity is recognized as notable or significant within a particular category or classification.
-
E.
ethnicCategoryIn
Indicates that an entity belongs to or is classified within a specified ethnic category in a given context.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abe6f0dc8190a1bebb5e21f4ceac |
completed | March 1, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7dfc5c8190890c9df485d73a86 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:38 p.m.