Triple
T7966253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yinxu |
E185214
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Anyang |
E77170
|
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: Anyang | Statement: [Yinxu, locatedIn, Anyang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anyang Context triple: [Yinxu, locatedIn, Anyang]
-
A.
Anyang
chosen
Anyang is an ancient city in northern China renowned as one of the historical capitals of the Shang dynasty and a major archaeological site.
-
B.
Anyang
Anyang is a mid-sized South Korean city in the Seoul Capital Area known for its residential districts, light industry, and proximity to central Seoul.
-
C.
Taian
Taian is a prefecture-level city in eastern China's Shandong province, best known as the gateway to the sacred Mount Tai.
-
D.
Luoyang
Luoyang is one of China’s oldest and most historically significant cities, renowned as an ancient imperial capital and cultural center along the Yellow River.
-
E.
Wu’an
Wu’an is a county-level city administered by Handan in Hebei Province, northern China, known for its industrial development and coal resources.
- 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_69ca8297699481909b75a405f01e03af |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ba262208190887169fe94e47b0e |
completed | March 31, 2026, 3:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd33cf48188190b57ac2fb1dbfa771 |
completed | April 1, 2026, 3:03 p.m. |
Created at: March 30, 2026, 5:12 p.m.