Triple
T12676781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuznetsov NK-144 |
E302833
|
entity |
| Predicate | usedOnConfiguration |
P72810
|
FINISHED |
| Object | four‑engine Tu-144 layout |
—
|
LITERAL 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: four‑engine Tu-144 layout | Statement: [Kuznetsov NK-144, usedOnConfiguration, four‑engine Tu-144 layout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedOnConfiguration Context triple: [Kuznetsov NK-144, usedOnConfiguration, four‑engine Tu-144 layout]
-
A.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
B.
usedOnMode
Indicates that something is applied, operated, or functions specifically in a given mode or operational setting.
-
C.
appliesToConfiguration
chosen
Indicates that something (such as a rule, setting, or operation) is relevant to, affects, or is intended for a particular configuration.
-
D.
usedOnPart
Indicates that something is applied to, operates on, or is intended for use with a specific part of a larger object or system.
-
E.
usedOnBrand
Indicates that something (such as a product, material, or element) is applied to, associated with, or utilized in connection with a particular brand.
- F. None of above.
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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961b0d9c88190a05d6cbcb7a1642d |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:20 p.m.