Triple
T32978765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl Moor |
E843740
|
entity |
| Predicate | relationshipToFranzMoor |
P205220
|
FINISHED |
| Object | antagonistic |
—
|
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: antagonistic | Statement: [Karl Moor, relationshipToFranzMoor, antagonistic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToFranzMoor Context triple: [Karl Moor, relationshipToFranzMoor, antagonistic]
-
A.
relationshipToFranKubelik
Indicates the specific type of personal or social relationship an entity has with Fran Kubelik.
-
B.
relationToVonMaur
Indicates a specified type of relationship or association that an entity has with Von Maur.
-
C.
relationshipToPármeno
Indicates the specific type of personal or social relationship that one entity has to Pármeno.
-
D.
relationshipWithAlbertDeMorcerf
Indicates that there exists some form of relationship, connection, or association between an entity and Albert de Morcerf.
-
E.
relationshipToFrancis
Indicates the specific familial, social, or professional connection that an entity has with Francis.
- 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_69f3494c6f9c8190a255409fce8b1d3b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037cab06288190b093935f235ddff2 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:22 a.m.