Triple
T38656329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan Cathedral of Jaro |
E939899
|
entity |
| Predicate | hasPlazaNearby |
P108855
|
FINISHED |
| Object | Jaro Plaza |
—
|
NE NERFINISHED |
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: Jaro Plaza | Statement: [Metropolitan Cathedral of Jaro, hasPlazaNearby, Jaro Plaza]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlazaNearby Context triple: [Metropolitan Cathedral of Jaro, hasPlazaNearby, Jaro Plaza]
-
A.
hasPlaza
Indicates that an entity includes, contains, or is associated with a plaza as part of its structure or grounds.
-
B.
hasAdjacentPlaza
chosen
Indicates that one place or structure is directly next to or bordering a plaza.
-
C.
hasPlazaAbove
Indicates that one entity has a plaza located directly above it in a vertical or structural sense.
-
D.
hasOutletNear
Indicates that one entity has a physical outlet or branch located in close proximity to another specified location or entity.
-
E.
hasAttractionNearby
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
- 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_69f76ede49648190a48bfe47032a05a3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
Created at: May 3, 2026, 4:33 p.m.