Triple
T18044186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fama–French three-factor model |
E431728
|
entity |
| Predicate | typicalHorizon |
P129590
|
FINISHED |
| Object | long-term average returns |
—
|
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: long-term average returns | Statement: [Fama–French three-factor model, typicalHorizon, long-term average returns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalHorizon Context triple: [Fama–French three-factor model, typicalHorizon, long-term average returns]
-
A.
horizonStructure
Indicates the structural or organizational characteristics that define how a horizon or boundary layer is formed, arranged, or composed.
-
B.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
C.
typicalAspect
Indicates that something represents a characteristic or commonly occurring aspect of another thing or situation.
-
D.
typicalVisibility
Indicates the usual or expected degree to which one entity can be seen or perceived from another under normal conditions.
-
E.
typicalHighestLevel
Indicates the usual or most common maximum level or degree that something typically reaches within a given context.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4bff13f488190993445769551c9c2 |
completed | April 19, 2026, 11:43 a.m. |
| PD | Predicate disambiguation | batch_69e3f908da508190a088aa837ea5b7af |
completed | April 18, 2026, 9:35 p.m. |
| PDg | Predicate description generation | batch_69e42d8eefa88190a700c7c1b4213e46 |
completed | April 19, 2026, 1:19 a.m. |
Created at: April 10, 2026, 10:25 a.m.