Triple
T27904998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Avenue |
E705744
|
entity |
| Predicate | inVicinityOf |
P61270
|
FINISHED |
| Object | Central Secretariat area |
—
|
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: Central Secretariat area | Statement: [South Avenue, inVicinityOf, Central Secretariat area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inVicinityOf Context triple: [South Avenue, inVicinityOf, Central Secretariat area]
-
A.
nearbyTo
Indicates that one entity is located close in distance or position to another entity.
-
B.
nearbyLocation
chosen
Indicates that one location is situated close to another location in physical space.
-
C.
meetsNear
Indicates that two entities meet or come together at a location that is in close proximity to a specified reference point or area.
-
D.
residesNear
Indicates that one entity lives or is located in close physical proximity to another entity.
-
E.
nearbyInfluence
Indicates that one entity affects or exerts influence on another due to being physically or spatially close to it.
- 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_69ef96b5aad08190be36a277c31e7004 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f63b317e048190963989b732b25b91 |
completed | May 2, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69f6370ea79c81909b761821ee0fa698 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 6:45 p.m.