Triple
T35546683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Owode |
E1027236
|
entity |
| Predicate | hasLocalGovernmentHeadquartersNearby |
P44325
|
FINISHED |
| Object | Ota |
—
|
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: Ota | Statement: [Owode, hasLocalGovernmentHeadquartersNearby, Ota]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalGovernmentHeadquartersNearby Context triple: [Owode, hasLocalGovernmentHeadquartersNearby, Ota]
-
A.
hasMunicipalitySeatNearby
Indicates that the municipality’s administrative seat is located in close proximity to the referenced place or entity.
-
B.
hasTribalHeadquartersNearby
Indicates that the subject entity is located close to the tribal headquarters of a Native nation or tribe.
-
C.
nearHeadquartersOf
chosen
Indicates that one entity is located geographically close to the headquarters of another entity.
-
D.
hasDepartmentCapitalNearby
Indicates that the subject entity has a departmental capital city located in close geographical proximity to it.
-
E.
isNearCapitalCity
Indicates that an entity is located close to, or in the immediate vicinity of, a capital city.
- 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_69f76e008ba08190927acd8e5e0344c8 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ff27b125948190aced0fe0189fd39a |
completed | May 9, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69ff26c30a0481909ef6a54ded851e42 |
completed | May 9, 2026, 12:21 p.m. |
Created at: May 3, 2026, 4:04 p.m.