Triple
T7251057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xianyang |
E157600
|
entity |
| Predicate | neighboringCity |
P988
|
FINISHED |
| Object | Xi’an |
E25916
|
NE 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: Xi’an | Statement: [Xianyang, neighboringCity, Xi’an]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Xi’an Context triple: [Xianyang, neighboringCity, Xi’an]
-
A.
Baoji
Baoji is a major industrial and transportation hub city in western Shaanxi Province, China, known for its manufacturing base and historical sites.
-
B.
Chang'an
Chang'an was the ancient capital of several Chinese dynasties and a major political, cultural, and trade center along the Silk Road.
-
C.
Xianyang, China
Xianyang is a historic city in Shaanxi Province, China, known as the former capital of the Qin dynasty and located near the modern metropolis of Xi’an.
-
D.
X’ian, China
chosen
Xi’an is a major historic city in central China, best known as the ancient capital of several dynasties and home to the famed Terracotta Army.
-
E.
Hanzhong
Hanzhong is a historic prefecture-level city in southwestern Shaanxi, China, known as a key gateway between northern and southern China and for its rich cultural and natural landscapes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6882d81d4819085f7ff862951ee4f |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ea791fec8190aee56ab4503770be |
completed | March 27, 2026, 8:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c802a61718819088cc2d37818af4ca |
completed | March 28, 2026, 4:32 p.m. |
Created at: March 27, 2026, 2:56 p.m.