Triple
T13677981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Old Fritz |
E327924
|
entity |
| Predicate | referentKnownFor |
P111120
|
FINISHED |
| Object | military reforms |
—
|
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: military reforms | Statement: [The Old Fritz, referentKnownFor, military reforms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: referentKnownFor Context triple: [The Old Fritz, referentKnownFor, military reforms]
-
A.
refersToPersonKnownFor
Indicates that one entity makes reference to a person who is notable or recognized for some specific role, achievement, or characteristic.
-
B.
namedForKnownFor
Indicates that one entity is named after another entity specifically because that other entity is notable or recognized for something.
-
C.
segmentKnownFor
Indicates that a specific segment or portion of something is recognized or notable for a particular characteristic, feature, or association.
-
D.
alsoKnownFor
Indicates that an entity is additionally recognized or noted for another work, role, achievement, or characteristic beyond its primary association.
-
E.
creatorKnownFor
Indicates that a creator is especially recognized or notable for a particular work, contribution, or achievement.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65d8dc081909664e69bb38610ba |
completed | April 12, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8d8d0881908d6e89954f44eed4 |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:53 p.m.