Triple
T37105173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Evpatoria RT-70 |
E918820
|
entity |
| Predicate | hasDishMount |
P34295
|
FINISHED |
| Object | alt-azimuth mount |
—
|
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: alt-azimuth mount | Statement: [Evpatoria RT-70, hasDishMount, alt-azimuth mount]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDishMount Context triple: [Evpatoria RT-70, hasDishMount, alt-azimuth mount]
-
A.
hasDiningComponent
Indicates that something includes or is associated with a dining-related part, feature, or function.
-
B.
hasMountingFeature
chosen
Indicates that one entity includes or provides a structural feature intended for mounting or attaching another entity.
-
C.
hasDishType
Indicates that an item (such as a food or menu entry) is classified as belonging to a particular type of dish (e.g., appetizer, main course, dessert).
-
D.
hasDiningFeature
Indicates that something possesses a specific characteristic, amenity, or attribute related to dining.
-
E.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
- 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_69f76e9b99c8819096164b21ff5bd996 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff80d9a1d88190a95b1488acd6e2e5 |
completed | May 9, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69ff802ae2dc819093a3cda42b63dcbd |
completed | May 9, 2026, 6:42 p.m. |
Created at: May 3, 2026, 4:14 p.m.