Triple
T20049071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 智忠 |
E499142
|
entity |
| Predicate | hasFirstCharacterPosition |
P137790
|
FINISHED |
| Object | 智 |
—
|
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: 智 | Statement: [智忠, hasFirstCharacterPosition, 智]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFirstCharacterPosition Context triple: [智忠, hasFirstCharacterPosition, 智]
-
A.
hasFirstTerm
Indicates that an entity is associated with a specific first term in an ordered sequence, period, or series.
-
B.
hasFirstContinuousTextFrom
Indicates that one entity provides the initial uninterrupted segment of text from which the other entity is derived or begins.
-
C.
hasSignificantCharacter
Indicates that an entity possesses a character or trait that is notably important, influential, or central within a given context.
-
D.
hasSequencePosition
chosen
Indicates that an element occupies a specific position or order within a sequence.
-
E.
hasCurrentCharacter
Indicates that an entity is associated with or possesses a specific character that is currently active or in use.
- 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_69da6276bcf48190aabbf279192a5fb4 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6632cccb481908278c8b2930a8c26 |
completed | April 20, 2026, 5:32 p.m. |
| PD | Predicate disambiguation | batch_69e54cee7a5c819084ae4ff26419833f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:37 p.m.