Triple
T8090459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emperor Zhang of Han |
E188844
|
entity |
| Predicate | eraNameUsage |
P2938
|
FINISHED |
| Object | used multiple era names during his reign |
—
|
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: used multiple era names during his reign | Statement: [Emperor Zhang of Han, eraNameUsage, used multiple era names during his reign]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eraNameUsage Context triple: [Emperor Zhang of Han, eraNameUsage, used multiple era names during his reign]
-
A.
nomenclaturalStatus
Indicates the formal taxonomic or naming status assigned to a scientific name (e.g., valid, invalid, synonym, provisional) within a nomenclatural system.
-
B.
taxonomicHistory
Indicates the historical sequence of taxonomic classifications or changes that an entity has undergone over time.
-
C.
eraName
chosen
Indicates the named historical or chronological era associated with an entity or time period.
-
D.
taxonomicAuthority
Indicates the entity that formally described, named, or classified another entity in a taxonomic context.
-
E.
usedTaxonomicSystem
Indicates that a particular taxonomic classification system was applied or followed when organizing or identifying the entities involved.
- 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_69ca82b7b3e88190b9041ab0ef28b3cb |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb421fb8348190b6495394d498d3f4 |
completed | March 31, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:29 p.m.