Triple
T9628522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baksan River |
E232532
|
entity |
| Predicate | localImportance |
P89351
|
FINISHED |
| Object | important waterway for local communities |
—
|
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: important waterway for local communities | Statement: [Baksan River, localImportance, important waterway for local communities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localImportance Context triple: [Baksan River, localImportance, important waterway for local communities]
-
A.
relativeImportanceInCountry
Indicates the comparative significance or priority of something within the context of a specific country.
-
B.
peakImportance
Indicates that something reaches or represents the highest level of importance within a given context or timeframe.
-
C.
localReputation
Indicates the perceived standing, trustworthiness, or esteem an entity holds within a specific local community or area.
-
D.
routeImportance
Indicates the relative significance or priority of a route compared to other possible routes, typically in terms of usefulness, relevance, or preference.
-
E.
relativeImportanceAtAirport
Indicates the comparative level of importance or priority assigned to entities within the context of an airport.
- F. None of above. chosen
Provenance (4 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_69ca848793ec8190a93a12383a754dc0 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b00162481908f396f6b6e470d6c |
completed | April 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69ccd5acfa5c8190aaba3cf548723604 |
completed | April 1, 2026, 8:22 a.m. |
| PDg | Predicate description generation | batch_69ccd93fc45c8190a823305e461e581d |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:10 p.m.