Triple
T13989182
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lux et Lex |
E336521
|
entity |
| Predicate | hasTwoKeyConcepts |
P112067
|
FINISHED |
| Object | light |
—
|
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: light | Statement: [Lux et Lex, hasTwoKeyConcepts, light]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTwoKeyConcepts Context triple: [Lux et Lex, hasTwoKeyConcepts, light]
-
A.
hasConcept
Indicates that an entity includes, embodies, or is associated with a particular concept.
-
B.
hasCriticalConcept
Indicates that one entity includes, depends on, or is defined by a key concept that is essential to understanding or functioning of another entity.
-
C.
hasConceptualParallel
Indicates that one entity corresponds to or mirrors another at a conceptual level, showing a similar idea, structure, or pattern despite possible differences in form or context.
-
D.
hasConceptualStructure
Indicates that one entity embodies, organizes, or is characterized by a particular conceptual structure defined by another entity.
-
E.
hasKeyDua
Indicates that one entity possesses or is associated with a specific secondary or backup key related to another 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb22e388190904fc87765176c91 |
completed | April 14, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69dd465dfbc4819090d8c61fd572d35f |
completed | April 13, 2026, 7:39 p.m. |
| PDg | Predicate description generation | batch_69de01ed2098819088ec45069f6f2609 |
completed | April 14, 2026, 8:59 a.m. |
Created at: April 9, 2026, 10:18 p.m.