Triple
T32304683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Treuhandanstalt |
E825330
|
entity |
| Predicate | numberOfEnterprisesManaged |
P17464
|
FINISHED |
| Object | over 8000 |
—
|
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: over 8000 | Statement: [Treuhandanstalt, numberOfEnterprisesManaged, over 8000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfEnterprisesManaged Context triple: [Treuhandanstalt, numberOfEnterprisesManaged, over 8000]
-
A.
hasNumberOfCompanies
chosen
Indicates the quantitative relationship specifying how many companies are associated with a given entity.
-
B.
hasNumberOfBusinessUnits
Indicates the specific count of business units associated with an entity.
-
C.
sectorManaged
Indicates that one entity is responsible for administering, overseeing, or directing the operations of a particular sector.
-
D.
numberOfPropertiesManaged
Indicates the total count of properties that an entity is responsible for managing.
-
E.
hasNumberOfAgencies
Indicates the quantity of agencies associated with or linked to a given entity.
- 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_69f349115304819084ee91d345b6c8aa |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a01a18e350481909f848686568d19bc |
completed | May 11, 2026, 9:29 a.m. |
| PD | Predicate disambiguation | batch_6a01a121b67c81908a6c5be9eb8e9ca5 |
completed | May 11, 2026, 9:28 a.m. |
Created at: May 1, 2026, 12:45 a.m.