Triple
T28490220
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ong |
E720943
|
entity |
| Predicate | correspondsToCharacter |
P63661
|
FINISHED |
| Object | 王 |
—
|
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: 王 | Statement: [Ong, correspondsToCharacter, 王]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToCharacter Context triple: [Ong, correspondsToCharacter, 王]
-
A.
characterCorrespondsTo
Indicates that one character is equivalent to, maps onto, or represents another character in a defined correspondence or mapping.
-
B.
correspondsToChineseCharacter
chosen
Indicates that one entity is the equivalent or representation of a specific Chinese written character.
-
C.
appliesToCharacter
Indicates that an action, rule, or property is specifically directed toward or relevant for a particular character.
-
D.
refersToCharacter
Indicates that one entity makes reference to, mentions, or points to a specific character as its subject.
-
E.
representedByCharacter
Indicates that one entity is depicted, symbolized, or personified by a particular character in a work or medium.
- 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_69f01a5a47148190b0a7e111bc432e0a |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f676c440708190a4b9974e95d2291a |
completed | May 2, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69f675fd59608190b246383435e68fce |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 28, 2026, 3:01 a.m.