Triple
T5232997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doctrine of the Mean |
E118153
|
entity |
| Predicate | attributedTo |
P806
|
FINISHED |
| Object |
Zisi
Zisi was an early Confucian philosopher, the grandson of Confucius, known for developing and transmitting key ideas in Confucian moral and metaphysical thought.
|
E504979
|
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: Zisi | Statement: [Doctrine of the Mean, attributedTo, Zisi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zisi Context triple: [Doctrine of the Mean, attributedTo, Zisi]
-
A.
Daisi
Daisi is a Georgian opera by composer Zakharia Paliashvili, renowned as one of the classics of Georgian national opera repertoire.
-
B.
Seia
Seia is a municipality and town in central Portugal known for its proximity to the Serra da Estrela mountains and natural park.
-
C.
Tzi
Tzi is the given name of Tzi Ma, a Hong Kong-American actor known for his roles in films like "Arrival" and "Rush Hour" and numerous television series.
-
D.
Shiso
Shiso is a small inland city in Japan’s Hyogo Prefecture known for its mountainous scenery, forests, and outdoor recreation.
-
E.
Kiesen
Kiesen is a municipality in the canton of Bern, Switzerland, served by a station on the Bern–Thun railway line.
- 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: Zisi Triple: [Doctrine of the Mean, attributedTo, Zisi]
Generated description
Zisi was an early Confucian philosopher, the grandson of Confucius, known for developing and transmitting key ideas in Confucian moral and metaphysical thought.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zisi Target entity description: Zisi was an early Confucian philosopher, the grandson of Confucius, known for developing and transmitting key ideas in Confucian moral and metaphysical thought.
-
A.
Daisi
Daisi is a Georgian opera by composer Zakharia Paliashvili, renowned as one of the classics of Georgian national opera repertoire.
-
B.
Seia
Seia is a municipality and town in central Portugal known for its proximity to the Serra da Estrela mountains and natural park.
-
C.
Tzi
Tzi is the given name of Tzi Ma, a Hong Kong-American actor known for his roles in films like "Arrival" and "Rush Hour" and numerous television series.
-
D.
Shiso
Shiso is a small inland city in Japan’s Hyogo Prefecture known for its mountainous scenery, forests, and outdoor recreation.
-
E.
Kiesen
Kiesen is a municipality in the canton of Bern, Switzerland, served by a station on the Bern–Thun railway line.
- 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_69bd4466fb8c819083b806a79414d7e4 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b0389048190b55b7c44fe657044 |
completed | March 20, 2026, 4:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef8154940819098ed76e14804f4b3 |
completed | March 21, 2026, 7:57 p.m. |
| NEDg | Description generation | batch_69bef8bfcd1c819090b81f8ebb097c5b |
completed | March 21, 2026, 8 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bef95e7ce48190a1ec2fc27ce37d00 |
completed | March 21, 2026, 8:02 p.m. |
Created at: March 20, 2026, 1:49 p.m.