Triple
T19385013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AAA |
E484910
|
entity |
| Predicate | typicalOutlook |
P136250
|
FINISHED |
| Object | stable |
—
|
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: stable | Statement: [AAA, typicalOutlook, stable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOutlook Context triple: [AAA, typicalOutlook, stable]
-
A.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
B.
typicalGoing
Indicates that an entity is engaged in or undergoing a normal, expected instance of going or movement from one place to another.
-
C.
typicalProfile
Indicates that an entity represents the standard or most representative profile or pattern for another entity.
-
D.
exchange
Indicates a reciprocal transfer of something (such as goods, information, or services) between two or more entities.
-
E.
officeScope
Indicates that a relationship, authority, or action is limited to, defined within, or applicable only in the context of a particular office or official position.
- F. None of above. chosen
Provenance (4 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b3ffa548190a060d6e94562a5d2 |
completed | April 20, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69e4fd602f008190aa9bc76ae17e4ce1 |
completed | April 19, 2026, 4:05 p.m. |
| PDg | Predicate description generation | batch_69e50213571881909cd7543a43b51986 |
completed | April 19, 2026, 4:25 p.m. |
Created at: April 10, 2026, 1:35 p.m.