Triple
T31154649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byzantine echoi |
E794168
|
entity |
| Predicate | numberOfPrincipalModes |
P144631
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [Byzantine echoi, numberOfPrincipalModes, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPrincipalModes Context triple: [Byzantine echoi, numberOfPrincipalModes, 8]
-
A.
typicalNumberOfComponents
Indicates the usual or standard count of distinct components that an entity is expected to have.
-
B.
hasNumberOfMainModes
chosen
Indicates the relationship that specifies how many primary or main modes (e.g., ways of operation or types) are associated with a given entity.
-
C.
basisVectorsCount
Indicates the number of basis vectors associated with a given vector space or basis.
-
D.
numberOfPrincipalRoles
Indicates the total count of primary or leading roles associated with a given entity.
-
E.
dimensionOfComponents
Indicates that a specified dimension value is associated with, or applies to, the components of an object or system.
- 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_69f224d41bb48190a5621cd1485e3a30 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a00c8e617548190bba4cdfbb6f512e0 |
completed | May 10, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_6a00c7e816b88190bd40f5ea2a768c8b |
completed | May 10, 2026, 6:01 p.m. |
Created at: April 29, 2026, 9:06 p.m.