Triple
T11846579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rybinsk |
E281792
|
entity |
| Predicate | hostsFacilityType |
P2836
|
FINISHED |
| Object | aircraft engine plant |
—
|
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: aircraft engine plant | Statement: [Rybinsk, hostsFacilityType, aircraft engine plant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hostsFacilityType Context triple: [Rybinsk, hostsFacilityType, aircraft engine plant]
-
A.
hasFacilityType
chosen
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
B.
hasHotelType
Indicates that a hotel is classified as belonging to a specific type or category (e.g., resort, boutique, hostel).
-
C.
housesFacility
Indicates that one entity serves as a location or container in which the other entity (a facility) is situated or operates.
-
D.
designedFacilityType
Indicates the type or category of facility that something (such as a plan, system, or component) is specifically designed for.
-
E.
hostsClassification
Indicates that an entity serves as the host or environment in which a particular classification or categorized item resides or is applied.
- 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_69d6ab287ba48190a5178779fd19b9b7 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a65b5ff08190bb58361f6a6acdca |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a254a57481908a1e6ad97919c416 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.