Triple
T37065518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ket language |
E917430
|
entity |
| Predicate | hasContact |
P205709
|
FINISHED |
| Object | Russian language |
E3584
|
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: Russian language | Statement: [Ket language, hasContact, Russian language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasContact Context triple: [Ket language, hasContact, Russian language]
-
A.
hasContactMethod
Indicates that an entity has a specific way or channel through which it can be contacted.
-
B.
hasKontakion
Indicates that an entity is associated with or possesses a specific kontakion, i.e., a particular liturgical hymn or chant.
-
C.
hasContactState
Indicates that an entity is currently in a specific state or condition regarding its physical or communicative contact with another entity.
-
D.
hasContactType
Indicates the specific kind or category of contact relationship that exists between two entities.
-
E.
hasContactRole
Indicates that an entity serves in a specific role or capacity as a contact for another entity.
- F. None of above. chosen
Provenance (5 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_69f76e95fa40819091e14681087ae5e4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3e8c58f82481908cc1f83258fc3526 |
completed | June 26, 2026, 2:27 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:14 p.m.