Triple
T13915023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tiantongyuan corridor |
E334598
|
entity |
| Predicate | hasNameInChineseCharacters |
P4878
|
FINISHED |
| Object | 天通苑走廊 |
—
|
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: 天通苑走廊 | Statement: [Tiantongyuan corridor, hasNameInChineseCharacters, 天通苑走廊]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameInChineseCharacters Context triple: [Tiantongyuan corridor, hasNameInChineseCharacters, 天通苑走廊]
-
A.
hasMultipleChineseCharacters
Indicates that the referenced item consists of more than one Chinese character.
-
B.
nameInChinese
chosen
Indicates that an entity has a specific written name or label expressed in the Chinese language.
-
C.
hasNameInJapanese
Indicates that an entity is associated with a specific name expressed in the Japanese language.
-
D.
hasUnicodeName
Indicates that an entity is associated with a specific official Unicode name assigned to a character or symbol.
-
E.
canRepresentMultipleChineseCharacters
Indicates that a given form (such as a sound, syllable, or written unit) is capable of corresponding to more than one distinct Chinese character.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de27260ae08190be45b4b15898e365 |
completed | April 14, 2026, 11:38 a.m. |
| PD | Predicate disambiguation | batch_69de059e4ba881908554f72e889719fa |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:16 p.m.