Triple
T9313236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | K-root |
E224054
|
entity |
| Predicate | hasLogicalIdentifierCount |
P88034
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [K-root, hasLogicalIdentifierCount, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLogicalIdentifierCount Context triple: [K-root, hasLogicalIdentifierCount, 1]
-
A.
hasNonLogicalSymbol
Indicates that a given formal system, expression, or language includes at least one symbol that is not part of its logical vocabulary (e.g., not a connective, quantifier, or equality sign).
-
B.
hasNumberOfLogicalServers
Indicates the quantity of logical servers associated with or contained within a given entity.
-
C.
hasLogicalStructure
Indicates that one entity possesses or exhibits a specific underlying logical organization or pattern defined by another entity.
-
D.
hasStructureCount
Indicates the number of structures associated with or contained by a given entity.
-
E.
haveIdentifier
Indicates that an entity is associated with a specific identifier used to uniquely reference or distinguish it.
- 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_69ca8425f4fc81909c1c586e9a5b7530 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd20b048a081909fd7ec0b6b863063 |
completed | April 1, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69cc7a61e9a4819096eb014f3791ef2e |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc955a38108190b602d1e73725f11b |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:37 p.m.