Triple
T18693522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tikka |
E457057
|
entity |
| Predicate | parentOrganization |
P254
|
FINISHED |
| Object | Sako |
—
|
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: Sako | Statement: [Tikka, parentOrganization, Sako]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sako Context triple: [Tikka, parentOrganization, Sako]
-
A.
Sako
chosen
Sako is a Finnish firearms manufacturer renowned for its high-quality rifles and precision engineering, operating as a subsidiary of Beretta.
-
B.
Sako
Sako is a surname most prominently associated with Louis Raphaël I Sako, the Chaldean Catholic Patriarch of Babylon and a leading figure in the modern Iraqi Christian community.
-
C.
Saker
Saker is a large, powerful falcon species native to Eurasia, known for its speed, hunting prowess, and use in traditional falconry.
-
D.
Soko
Soko is a French singer-songwriter and actress known for her emotionally raw music and roles in independent films.
-
E.
Karrabin
Karrabin is a rural-residential locality in the western outskirts of Ipswich, Queensland, Australia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e562e581f48190997d279296a31e7f |
completed | April 19, 2026, 11:19 p.m. |
Created at: April 10, 2026, 11:49 a.m.