Triple
T15355399
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Comnidyne |
E367159
|
entity |
| Predicate | hasFictionalHierarchy |
P118240
|
FINISHED |
| Object | corporate management structure |
—
|
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: corporate management structure | Statement: [Comnidyne, hasFictionalHierarchy, corporate management structure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalHierarchy Context triple: [Comnidyne, hasFictionalHierarchy, corporate management structure]
-
A.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
B.
hasFictionalForm
Indicates that an entity has a counterpart or representation that exists within a fictional or imaginary context.
-
C.
hasFictionalScope
Indicates that something pertains to, applies within, or is limited to a fictional or imagined context rather than real-world scope.
-
D.
hasFictionalUniverseElement
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
-
E.
hasFictionalEstablishmentType
Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e2c00648190ae2325e1ee58dcfd |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69deca991e5081908b0df3d1ee7d5338 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2e413481909d9180a8d78d2c17 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:18 a.m.