Triple
T2601503
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IS-LM model |
E58352
|
entity |
| Predicate | horizontalAxis |
P39553
|
FINISHED |
| Object | real output |
—
|
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: real output | Statement: [IS-LM model, horizontalAxis, real output]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: horizontalAxis Context triple: [IS-LM model, horizontalAxis, real output]
-
A.
usesAxis
Indicates that one entity employs or relies on another entity as a reference axis or basis for orientation, measurement, or organization.
-
B.
primaryAxisFormation
Indicates the process or relationship by which the main structural or organizational axis of a system, body, or object is established or developed.
-
C.
isMajorAxisFor
Indicates that something serves as the primary or longest axis that defines the main directional or structural orientation of another object or system.
-
D.
targetVertical
Indicates that one entity is directed toward, aligned with, or intended for a specific vertical market, domain, or industry segment.
-
E.
countryOnAxisSide
Indicates that a country was aligned with or belonged to the Axis side in a particular conflict or war.
- 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_69ab4ac14040819098b13f4a27d5c8ff |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd4587014819089f78e93adf2144c |
completed | March 7, 2026, 7:31 a.m. |
| PD | Predicate disambiguation | batch_69abd0d4e8648190b612eb09aa085451 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd1c7b6e48190be9a0c31069df797 |
completed | March 7, 2026, 7:20 a.m. |
Created at: March 6, 2026, 9:49 p.m.