Triple
T11871304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chángzhēng |
E282412
|
entity |
| Predicate | representsChineseTerm |
P41219
|
FINISHED |
| Object | 长征 |
—
|
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: 长征 | Statement: [Chángzhēng, representsChineseTerm, 长征]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representsChineseTerm Context triple: [Chángzhēng, representsChineseTerm, 长征]
-
A.
correspondsToChineseCharacter
Indicates that one entity is the equivalent or representation of a specific Chinese written character.
-
B.
ChinesePinyin
chosen
Indicates that one entity is the Chinese pinyin (romanized phonetic transcription) representation of another entity.
-
C.
ChineseNameTraditional
Indicates that an entity’s name is given in traditional Chinese characters.
-
D.
characterUnicodeSimplified
Indicates that one entity is the simplified-Unicode character form corresponding to another character entity.
-
E.
ChineseObjective
Indicates that an entity has an objective, goal, or target specifically related to China or the Chinese context.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d39d2934819093b9f7006f45e5cb |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:43 p.m.