Triple
T13587987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sanbao Gong |
E324618
|
entity |
| Predicate | meaningOfTitleComponentGong |
P16024
|
FINISHED |
| Object | Duke or Lord |
—
|
LITERAL 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: Duke or Lord | Statement: [Sanbao Gong, meaningOfTitleComponentGong, Duke or Lord]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meaningOfTitleComponentGong Context triple: [Sanbao Gong, meaningOfTitleComponentGong, Duke or Lord]
-
A.
titleMeaning
Indicates that one entity expresses or explains the meaning, significance, or interpretation of another entity’s title.
-
B.
meaningComponent
chosen
Indicates that one entity represents a semantic or conceptual component contributing to the overall meaning of another entity.
-
C.
meaningComponent郎
Indicates that one entity is a semantic component or constituent part of the overall meaning of another entity.
-
D.
oniMeaning
Indicates that one entity expresses or conveys the meaning or sense of another entity (such as a word, phrase, or symbol).
-
E.
symbolicGarnishMeaning
Indicates that a garnish is used to convey a symbolic or metaphorical meaning beyond its decorative or flavor-enhancing role.
- F. None of above.
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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb054c6008190839384ce26e8f71a |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.