Triple
T708052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 57th Street–Seventh Avenue station |
E14143
|
entity |
| Predicate | localeType |
P19051
|
FINISHED |
| Object | cultural district |
—
|
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: cultural district | Statement: [57th Street–Seventh Avenue station, localeType, cultural district]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localeType Context triple: [57th Street–Seventh Avenue station, localeType, cultural district]
-
A.
locale
Indicates that one entity is the place, setting, or geographic area in which another entity exists, occurs, or is situated.
-
B.
languageZone
Indicates the linguistic region or area in which a language is predominantly used or officially recognized.
-
C.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
D.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
E.
languageFamilyCode
Indicates the language family to which a given language belongs, represented by a standardized code.
- 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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5c011948190b2cfccd8fe722742 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f0217081908268b3f47e72f8df |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a5bed20c81909ecc28bf42594e72 |
completed | March 1, 2026, 8:46 p.m. |
Created at: March 1, 2026, 7:36 p.m.