Triple
T26528430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pleberio |
E670753
|
entity |
| Predicate | relationshipToMelibea |
P197253
|
FINISHED |
| Object | father |
—
|
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: father | Statement: [Pleberio, relationshipToMelibea, father]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToMelibea Context triple: [Pleberio, relationshipToMelibea, father]
-
A.
relationshipToCreature
Indicates a specified type of relational connection that one entity has toward a particular creature.
-
B.
relationshipToPármeno
Indicates the specific type of personal or social relationship that one entity has to Pármeno.
-
C.
relationshipToKlaatu
Indicates the specific familial, social, or professional relationship that one entity has to the entity named Klaatu.
-
D.
relationshipToEva
Indicates a specified type of personal or social relationship that an entity has with Eva.
-
E.
relationshipToHumans
Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
- 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_69eeb31ea1e08190b9ff43cf9bc25bf8 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69fe831c97c88190b27ecf100e25c2a0 |
completed | May 9, 2026, 12:43 a.m. |
| PD | Predicate disambiguation | batch_69fe7f1b92648190b14e56bcaee5d0ca |
completed | May 9, 2026, 12:26 a.m. |
| PDg | Predicate description generation | batch_69fe831ba4708190a5564afd7d5a4319 |
completed | May 9, 2026, 12:43 a.m. |
Created at: April 27, 2026, 1:33 a.m.