Triple
T1407438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isaac |
E31724
|
entity |
| Predicate | logicalTrait |
P27675
|
FINISHED |
| Object | highly analytical |
—
|
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: highly analytical | Statement: [Isaac, logicalTrait, highly analytical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: logicalTrait Context triple: [Isaac, logicalTrait, highly analytical]
-
A.
logicalPolarity
Indicates that the truth value of a statement is affirmed (positive) or denied (negative) relative to some logical context.
-
B.
logicSystem
Indicates a relationship where an entity is associated with, defined within, or governed by a particular logical framework or system of formal reasoning.
-
C.
hasLinguisticFeature
Indicates that an entity possesses a particular linguistic property, trait, or characteristic.
-
D.
logicalLevel
Indicates the relative position or depth of something within a hierarchy of abstraction, reasoning, or logical structure.
-
E.
linguisticFeature
Indicates a relationship where a linguistic property, pattern, or characteristic is attributed to or associated with a language-related entity (such as a word, phrase, or text).
- 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3bf7f0c8190aee96818de6ff4a5 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bf030a388190bc82d30b9233e873 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c11067b48190bca6ef3ac1475c20 |
completed | March 1, 2026, 10:43 p.m. |
Created at: March 1, 2026, 7:59 p.m.