Triple
T23744335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emperor Zhongzong of Tang |
E586770
|
entity |
| Predicate | eraNameUsedInDocuments |
P153532
|
FINISHED |
| Object | Jinglong |
—
|
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: Jinglong | Statement: [Emperor Zhongzong of Tang, eraNameUsedInDocuments, Jinglong]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eraNameUsedInDocuments Context triple: [Emperor Zhongzong of Tang, eraNameUsedInDocuments, Jinglong]
-
A.
eraName
Indicates the named historical or chronological era associated with an entity or time period.
-
B.
eraNameType
Indicates the type or classification of a named historical or chronological era associated with an entity.
-
C.
eraNameInJapanese
Indicates the Japanese-language name used for a specific historical or calendar era.
-
D.
namedAccordingTo
Indicates that one entity is given a name that follows, references, or is derived from another entity or source.
-
E.
eraNameUsedDuringReign
Indicates that a particular era name was officially used throughout the duration of a ruler's reign.
- 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_69e24908efb08190bf755c3a9b91f222 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bcbcc4f88190a00fceeafbfb5cfd |
completed | April 29, 2026, 8:09 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
| PDg | Predicate description generation | batch_69f15adb23d88190ac2632299c26a9b3 |
completed | April 29, 2026, 1:11 a.m. |
Created at: April 17, 2026, 7:12 p.m.