Triple
T28075761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Longzhong Plan |
E709537
|
entity |
| Predicate | locationOfFormulation |
P13661
|
FINISHED |
| Object | Longzhong |
—
|
NE NERFINISHED |
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: Longzhong | Statement: [Longzhong Plan, locationOfFormulation, Longzhong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationOfFormulation Context triple: [Longzhong Plan, locationOfFormulation, Longzhong]
-
A.
locationFormed
chosen
Indicates the place or geographic area where an entity (such as an organization, group, or structure) was originally established or came into existence.
-
B.
exampleFormulation
Indicates that one entity serves as a representative or illustrative formulation or expression of another entity.
-
C.
hasFormulation
Indicates that one entity is expressed, prepared, or configured in a particular form or composition defined by another entity.
-
D.
formulatedIn
Indicates that something was created, developed, or expressed within a particular context, place, or framework.
-
E.
hasFormulationStrength
Indicates the specific strength or concentration associated with a particular formulation of a product or substance.
- F. None of above.
Provenance (3 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_69ef9b6f8078819098b741274cd1a2ee |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69ff3e1762d8819089a60e402e682817 |
completed | May 9, 2026, 2 p.m. |
| PD | Predicate disambiguation | batch_69ff3d8c6f308190a0646b1432752eb8 |
completed | May 9, 2026, 1:58 p.m. |
Created at: April 27, 2026, 8:48 p.m.