Triple
T23376443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chitose-ame |
E593618
|
entity |
| Predicate | associatedWithAge |
P51855
|
FINISHED |
| Object | 3 years |
—
|
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: 3 years | Statement: [Chitose-ame, associatedWithAge, 3 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithAge Context triple: [Chitose-ame, associatedWithAge, 3 years]
-
A.
containsAge
chosen
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
B.
associatedWithRetirement
Indicates a relationship in which something is connected to, involved in, or relevant to the state, process, or context of retirement.
-
C.
associatedWithTime
Indicates a relationship where something is linked or connected to a specific point or period in time.
-
D.
associatedWithStand
Indicates a relationship where an entity is linked or connected to a particular stand, such as being located at, operating in, or otherwise related to that stand.
-
E.
ageCorrelation
Indicates a statistical relationship between the ages of two entities, showing how changes in one entity’s age are associated with changes in the other’s.
- 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_69e25d268a50819095f2fd479da8ef3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a3b3cc348190953d0b0ebac9c5dd |
completed | April 29, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69f061c7aaa48190a58ce93f87155ffc |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:33 p.m.