Triple
T9779494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bogotá–Tenjo corridor |
E237329
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Tenjo |
E37138
|
NE 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: Tenjo | Statement: [Bogotá–Tenjo corridor, connects, Tenjo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tenjo Context triple: [Bogotá–Tenjo corridor, connects, Tenjo]
-
A.
Tenjo
chosen
Tenjo is a small municipality and town in the department of Cundinamarca, Colombia, known for its rural landscapes and proximity to Bogotá.
-
B.
Tenjo
Tenjo is a district in West Java, Indonesia, known as part of the greater Bogor area on the outskirts of Jakarta.
-
C.
Tokoro
Tokoro is a coastal district of Kitami City in Hokkaido, Japan, known historically for its fishing industry and drift ice along the Sea of Okhotsk.
-
D.
Toran
Toran is a given name that can be used for individuals in various cultures and contexts.
-
E.
Tokoname
Tokoname is a coastal city in Aichi Prefecture, Japan, historically renowned as one of the country’s Six Ancient Kilns for its distinctive ceramic and pottery production.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca84d975a08190aab25b02a89bdab3 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda13663f081909b95563038eb6485 |
completed | April 1, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bd28b0e48190984cf44d88f324d7 |
completed | April 5, 2026, 1:38 a.m. |
Created at: March 30, 2026, 8:27 p.m.