Triple
T1231484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grozny |
E26451
|
entity |
| Predicate | wasDescribedAs |
P21265
|
FINISHED |
| Object | one of the most destroyed cities in the world in the early 2000s |
—
|
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: one of the most destroyed cities in the world in the early 2000s | Statement: [Grozny, wasDescribedAs, one of the most destroyed cities in the world in the early 2000s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasDescribedAs Context triple: [Grozny, wasDescribedAs, one of the most destroyed cities in the world in the early 2000s]
-
A.
describedByAuthorAs
Indicates that one entity is characterized, labeled, or portrayed in a particular way by an author.
-
B.
isFrequentlyDescribedAs
chosen
Indicates that something is often characterized or referred to using a particular description or set of attributes.
-
C.
describedIn
Indicates that information about an entity is contained or documented within a specified source, such as a text, document, or media.
-
D.
describes
Indicates that one entity provides an explanation, representation, or account of another entity or concept.
-
E.
wasA
Indicates that an entity previously had a certain role, type, or classification in the past.
- 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_69a4948571c88190a9191e451e6035fd |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be5a25348190a0665b6324c4d8f5 |
completed | March 1, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69a4bb65d61c8190bf0424ea0019a98b |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.