Triple
T382720
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imperial double-headed eagle of Russia |
E8714
|
entity |
| Predicate | hasCrownCount |
P10695
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Imperial double-headed eagle of Russia, hasCrownCount, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrownCount Context triple: [Imperial double-headed eagle of Russia, hasCrownCount, 3]
-
A.
hasCrownName
Indicates that an entity possesses or is identified by a specific crown name, typically used as an official or regal title.
-
B.
crownedWith
Indicates that one entity serves as a crown, top, or decorative upper covering placed upon another entity.
-
C.
hasRoyalHouse
Indicates that an entity is associated with or belongs to a particular royal house or dynasty.
-
D.
hasRoyalConnection
Indicates a relationship where an entity is linked or associated in some notable way to royalty, a royal family, or a royal institution.
-
E.
hasNumberOfRulers
Indicates the quantity of rulers associated with or governing a given entity.
- 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_69a2e7f47dd08190a4e294ccbbe46cd4 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec40ff8c81909306eb2dfe1512af |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e96602188190b0cbc167f55a9237 |
completed | Feb. 28, 2026, 1:11 p.m. |
| PDg | Predicate description generation | batch_69a2ea2dc3088190a2aeb4496aff3582 |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.