Triple
T31755021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Veld Koning Machinefabriek |
E810533
|
entity |
| Predicate | relationToVekoma |
P207511
|
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: [Veld Koning Machinefabriek, relationToVekoma, predecessor company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationToVekoma Context triple: [Veld Koning Machinefabriek, relationToVekoma, predecessor company]
-
A.
relationToVonMaur
Indicates a specified type of relationship or association that an entity has with Von Maur.
-
B.
relationToUTMB
Indicates a relationship or association that an entity has with UTMB (e.g., affiliation, connection, or relevance to UTMB).
-
C.
relationshipToEva
Indicates a specified type of personal or social relationship that an entity has with Eva.
-
D.
relationToWSBK
Indicates a specified type of relationship or association that an entity has with WSBK.
-
E.
relationshipToPula
Indicates the type or nature of a relationship that an entity has with Pula.
- 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_69f348e340d48190b780fae618c51464 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e7aa0c8190bdc9ee4d54fc821b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 30, 2026, 11:29 p.m.