Triple
T34773904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anxi Protectorate |
E1002447
|
entity |
| Predicate | hasOfficialTitleInChinese |
P51900
|
FINISHED |
| Object | 安西都護府 |
—
|
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: 安西都護府 | Statement: [Anxi Protectorate, hasOfficialTitleInChinese, 安西都護府]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOfficialTitleInChinese Context triple: [Anxi Protectorate, hasOfficialTitleInChinese, 安西都護府]
-
A.
honorificTitleInChinese
Indicates that one entity is the honorific or respectful title used in Chinese to refer to another entity.
-
B.
hasChineseTitle
chosen
Indicates that an entity possesses a title or name expressed in the Chinese language.
-
C.
officeHolderTitleInChinese
Indicates the Chinese-language title or designation held by an office holder in a given position or role.
-
D.
usedChineseImperialTitles
Indicates that an entity employed official titles from the traditional Chinese imperial hierarchy in reference to another entity.
-
E.
hasOfficialNameInJapanese
Indicates that an entity has an official, formally recognized name expressed in the Japanese language.
- 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_69f76db30a108190bb57ca95b873e5bb |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 3:59 p.m.