Triple
T38243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Osaka Prefecture |
E757
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object |
Yao
Yao is a city in Osaka Prefecture, Japan, known as an industrial and residential hub within the Kansai region.
|
E6680
|
NE FINISHED |
How this triple was built (4 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: Yao | Statement: [Osaka Prefecture, hasMajorCity, Yao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yao Context triple: [Osaka Prefecture, hasMajorCity, Yao]
-
A.
Langche Zeng
Langche Zeng is a political scientist and quantitative methodologist known for his collaborative work with Gary King on statistical methods in social science research.
-
B.
Koba
Koba was a revolutionary alias used by Joseph Stalin during his early political activities in the Bolshevik movement.
-
C.
Wuling
Wuling is a Chinese automotive marque known for producing affordable compact cars and microvans, marketed through a joint venture involving General Motors.
-
D.
Kobe
Kobe is a major port city in Japan’s Kansai region, known for its scenic harbor setting, cosmopolitan atmosphere, and famous Kobe beef.
-
E.
Namba
Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Yao Triple: [Osaka Prefecture, hasMajorCity, Yao]
Generated description
Yao is a city in Osaka Prefecture, Japan, known as an industrial and residential hub within the Kansai region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Yao Target entity description: Yao is a city in Osaka Prefecture, Japan, known as an industrial and residential hub within the Kansai region.
-
A.
Langche Zeng
Langche Zeng is a political scientist and quantitative methodologist known for his collaborative work with Gary King on statistical methods in social science research.
-
B.
Koba
Koba was a revolutionary alias used by Joseph Stalin during his early political activities in the Bolshevik movement.
-
C.
Wuling
Wuling is a Chinese automotive marque known for producing affordable compact cars and microvans, marketed through a joint venture involving General Motors.
-
D.
Kobe
Kobe is a major port city in Japan’s Kansai region, known for its scenic harbor setting, cosmopolitan atmosphere, and famous Kobe beef.
-
E.
Namba
Namba is a major commercial and entertainment district in Osaka, Japan, known for its bustling nightlife, shopping, and iconic neon-lit streets.
- F. None of above. chosen
Provenance (5 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24acd14b48190b80d4329621583df |
completed | Feb. 28, 2026, 1:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a25ab3438c81908ff16eb23a09fea7 |
completed | Feb. 28, 2026, 3:02 a.m. |
| NEDg | Description generation | batch_69a25ba68f1081908f88d2bb2af35af6 |
completed | Feb. 28, 2026, 3:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a25c4a5fa8819082a737e1f0251a8a |
completed | Feb. 28, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.