Triple
T10705441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamaica–179th Street |
E252389
|
entity |
| Predicate | hasLocalNameVariant |
P24351
|
FINISHED |
| Object | 179th Street–Jamaica |
—
|
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: 179th Street–Jamaica | Statement: [Jamaica–179th Street, hasLocalNameVariant, 179th Street–Jamaica]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalNameVariant Context triple: [Jamaica–179th Street, hasLocalNameVariant, 179th Street–Jamaica]
-
A.
hasLocalNameFor
chosen
Indicates that one entity serves as the local or context-specific name or label used to refer to another entity.
-
B.
hasLocalName
Indicates that an entity is known by a specific name or designation within a particular local language, script, or regional context.
-
C.
hasOfficialNameVariant
Indicates that an entity has an alternative official form or version of its name.
-
D.
hasNoWidelyUsedLocalName
Indicates that the entity does not have a commonly used or widely recognized name in the local language or region.
-
E.
hasNameInLocalLanguage
Indicates that an entity is associated with a name expressed in the local or native language of a given context or region.
- 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_69d6aa5cbabc8190973e683950d89faf |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fddeb060819094cd125a68070eb2 |
completed | April 9, 2026, 1:16 a.m. |
| PD | Predicate disambiguation | batch_69d6dd8ea6408190a800f9cb57372189 |
completed | April 8, 2026, 10:58 p.m. |
Created at: April 8, 2026, 9:12 p.m.