Triple
T33950771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khodynka Tragedy |
E870432
|
entity |
| Predicate | hasCoronationCity |
P93978
|
FINISHED |
| Object | Moscow |
E1747
|
NE 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: Moscow | Statement: [Khodynka Tragedy, hasCoronationCity, Moscow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoronationCity Context triple: [Khodynka Tragedy, hasCoronationCity, Moscow]
-
A.
hasCoronationRitual
Indicates that an entity is associated with a specific formal ceremony or set of rites used to crown or inaugurate a ruler or leader.
-
B.
capitalOfCoronationEmpire
Indicates that a city or location serves as the capital of the Coronation Empire.
-
C.
hasRoyalCapital
Indicates that a place serves as the primary seat of royal authority or the official capital of a monarchy for a given entity.
-
D.
hasCoronationSubject
Indicates that an entity serves as the subject (the person or figure being crowned) in a coronation event.
-
E.
capitalOfCoronationCountryAtTime
chosen
Indicates that a city served as the capital of a specified country at the time when a particular coronation took place.
- F. None of above.
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_69f3499c2d7481909c953a5010227725 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a36a01e68a481909266a197c3b96354 |
completed | June 20, 2026, 2:13 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:49 a.m.