Triple
T17121857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Petersen & Sons Dry Goods Company |
E415486
|
entity |
| Predicate | relationToVonMaur |
P126059
|
FINISHED |
| Object | predecessor company |
—
|
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: predecessor company | Statement: [Petersen & Sons Dry Goods Company, relationToVonMaur, predecessor company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationToVonMaur Context triple: [Petersen & Sons Dry Goods Company, relationToVonMaur, predecessor company]
-
A.
relationshipToRelative
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
-
B.
relationshipToMother
Indicates the specific familial or social connection an entity has to its mother.
-
C.
relationToVonNeumann
Indicates a relationship in which one entity is connected or related in some specified way to John von Neumann.
-
D.
relationToAncestors
Indicates a familial relationship that connects an entity to one or more of its ancestors in a lineage or hierarchy.
-
E.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
- 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_69d886d090cc8190a39cb94992586905 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3e809ee888190a2cf69d59c0b9c20 |
completed | April 18, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69e35d6d20808190a38bb32e2294bc48 |
completed | April 18, 2026, 10:31 a.m. |
| PDg | Predicate description generation | batch_69e37542d060819082aa73948eb8ebd4 |
completed | April 18, 2026, 12:12 p.m. |
Created at: April 10, 2026, 5:36 a.m.