Triple
T16009436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Will Parry |
E388300
|
entity |
| Predicate | fatherAlias |
P93919
|
FINISHED |
| Object | Jopari |
E997518
|
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: Jopari | Statement: [Will Parry, fatherAlias, Jopari]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jopari Context triple: [Will Parry, fatherAlias, Jopari]
-
A.
Jopari
chosen
Jopari is the name used by Colonel John Parry, a key explorer and shamanic figure in Philip Pullman’s "His Dark Materials" series.
-
B.
Japeri
Japeri is a municipality in the state of Rio de Janeiro, Brazil, known for its location in the Baixada Fluminense region and its role as a railway hub.
-
C.
Jopara
Jopara is a mixed language spoken in Paraguay that blends Guaraní and Spanish in everyday communication.
-
D.
Surobi
Surobi is a town and district in eastern Afghanistan, strategically located along the Kabul River and a key site for nearby hydroelectric infrastructure.
-
E.
Kipoi
Kipoi is a traditional stone-built village in the Zagori region of Epirus, northwestern Greece, known for its arched bridges and well-preserved architecture.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1828e9e708190aec0078913bf098a |
completed | April 17, 2026, 12:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf24a9d8819083d7b11d71442da6 |
completed | May 10, 2026, 12:19 a.m. |
Created at: April 10, 2026, 4:55 a.m.