Triple
T12408813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yan Zhengzai |
E296459
|
entity |
| Predicate | placeOfResidence |
P75
|
FINISHED |
| Object | Lu |
E142972
|
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: Lu | Statement: [Yan Zhengzai, placeOfResidence, Lu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lu Context triple: [Yan Zhengzai, placeOfResidence, Lu]
-
A.
Lu
chosen
Lu is the traditional abbreviation and historical name used to refer to China’s Shandong province.
-
B.
Lu
Lu is a common Chinese surname with historical roots and numerous notable bearers across politics, academia, and the arts.
-
C.
LU
LU is the two-letter ISO 3166-1 alpha-2 country code assigned to Luxembourg for international identification and data standards.
-
D.
LU
LU is the vehicle registration code for the German city of Ludwigshafen am Rhein in the state of Rhineland-Palatinate.
-
E.
LU
LU is the commonly used abbreviation for the University of Latvia, a major public research university in Riga.
- 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94d4b86c88190afba0de15b34eee9 |
completed | April 10, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63488cac08190a81b2151c827932e |
completed | May 2, 2026, 5:29 p.m. |
Created at: April 8, 2026, 9:55 p.m.