Triple
T37557879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Origins of Political Order |
E933739
|
entity |
| Predicate | hasSequelScope |
P202494
|
FINISHED |
| Object | sequel covers period from French Revolution to the present |
—
|
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: sequel covers period from French Revolution to the present | Statement: [The Origins of Political Order, hasSequelScope, sequel covers period from French Revolution to the present]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSequelScope Context triple: [The Origins of Political Order, hasSequelScope, sequel covers period from French Revolution to the present]
-
A.
hasSubsequent
Indicates that one entity occurs, appears, or is positioned after another in a defined sequence or order.
-
B.
hasSequelType
Indicates that one work has a sequel of a specified type or category in relation to another work.
-
C.
hasSequelRole
Indicates that an entity plays a corresponding or continued role in a sequel to an earlier work.
-
D.
hasSequelElement
Indicates that one element is a sequel or subsequent installment to another element in a series or sequence.
-
E.
hasSequelLikeCycle
Indicates that a work is part of a sequence where sequels form a cycle, such that following the sequel relationships eventually leads back to the original work.
- 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_69f76ecb4acc8190b53f96d0b013e415 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a008ac37dc081908d360574912f40ec |
completed | May 10, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_6a008a67d73881909855ab4cfca3c399 |
completed | May 10, 2026, 1:38 p.m. |
| PDg | Predicate description generation | batch_6a008ac2d0dc8190865ccedb2003d0ed |
completed | May 10, 2026, 1:40 p.m. |
Created at: May 3, 2026, 4:17 p.m.