Triple
T13453091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pando Department |
E311159
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Cobija |
E124821
|
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: Cobija | Statement: [Pando Department, capital, Cobija]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cobija Context triple: [Pando Department, capital, Cobija]
-
A.
Cobija
chosen
Cobija is a small Bolivian city in the Amazon rainforest near the border with Brazil, known as an important regional center for trade and rubber production.
-
B.
Kasur
Kasur is a historic city in Pakistan’s Punjab province, renowned as the home and burial place of the Sufi poet Bulleh Shah.
-
C.
Siirt blanket
The Siirt blanket is a traditional Turkish woolen blanket, often made from mohair, renowned for its warmth, softness, and distinctive regional craftsmanship.
-
D.
Lucignolo
Lucignolo is the Italian name for Lampwick, a mischievous boy from Carlo Collodi’s "The Adventures of Pinocchio" who leads Pinocchio into trouble.
-
E.
Tiège
Tiège is a village in the municipality of Jalhay in the province of Liège, Belgium.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaefae85481909e6a59797cbb25e7 |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7399c539c819080802b620da6fcfc |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 9, 2026, 9:41 p.m.