Triple
T382725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imperial double-headed eagle of Russia |
E8714
|
entity |
| Predicate | orientationOfHeads |
P1101
|
FINISHED |
| Object | one head facing east |
—
|
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 head facing east | Statement: [Imperial double-headed eagle of Russia, orientationOfHeads, one head facing east]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: orientationOfHeads Context triple: [Imperial double-headed eagle of Russia, orientationOfHeads, one head facing east]
-
A.
orientation
chosen
Indicates the relative directional alignment or facing of one entity with respect to another or to a reference frame.
-
B.
heads
Indicates that one entity leads, directs, or is in charge of another entity, such as an organization, group, or initiative.
-
C.
arrowCount
Indicates the number of arrows associated with or involved in a given entity or interaction.
-
D.
sessionOrientation
Indicates the directional or spatial alignment relationship established between entities within a session or interaction context.
-
E.
offsets
Indicates that one entity counterbalances, compensates for, or reduces the effect, value, or impact of another.
- 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_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. |
Created at: Feb. 28, 2026, 1:08 p.m.