Triple
T6817110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Park Avenue |
E156791
|
entity |
| Predicate | hasAlternateNameSection |
P627
|
FINISHED |
| Object | Fourth Avenue continuation |
—
|
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: Fourth Avenue continuation | Statement: [Park Avenue, hasAlternateNameSection, Fourth Avenue continuation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternateNameSection Context triple: [Park Avenue, hasAlternateNameSection, Fourth Avenue continuation]
-
A.
hasSectionKnownAs
chosen
Indicates that an entity includes a section or part that is referred to by a specific name.
-
B.
hasTitleHolderAlternativeName
Indicates that an entity serving as a title holder is known by an alternative or additional name.
-
C.
hasAlternativeNameOfOrder
Indicates that one entity is an alternative or variant name used to refer to the same order as the other entity.
-
D.
hasAlternativeReferent
Indicates that an entity can also be referred to or identified by an alternative name, label, or reference.
-
E.
hasAlternativeNameForSameCity
Indicates that one city name is an alternative or variant name referring to the same city as another name.
- 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_69c688298a288190af3f285d57f76bbe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d354177481908ab3cf5437c095e2 |
completed | March 27, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_69c6d09bb4f881909bf20c188cb3e8e1 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:17 p.m.