Triple
T14215185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephano |
E352330
|
entity |
| Predicate | relationshipToTrinculo |
P113245
|
FINISHED |
| Object | drinking companion |
—
|
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: drinking companion | Statement: [Stephano, relationshipToTrinculo, drinking companion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToTrinculo Context triple: [Stephano, relationshipToTrinculo, drinking companion]
-
A.
relationshipToSanchoPanza
Indicates the specific type of relationship or connection an entity has to Sancho Panza.
-
B.
relationshipToEsmeralda
Indicates the specific type of relationship or connection an entity has to Esmeralda.
-
C.
relationshipWithManolin
Indicates a relationship or connection that exists between an entity and Manolin, such as a bond, association, or interaction involving him.
-
D.
relationshipToAhab
Indicates the specific type of personal or social connection an entity has with Ahab.
-
E.
relationshipToElizabethSwann
Indicates the specific interpersonal or familial connection an entity has with Elizabeth Swann.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de620f07bc81909212dcd1c91b5f95 |
completed | April 14, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69de05bcd7d48190a4848d9320404aa6 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de239a02e881909b0e2679487e4ab2 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 10, 2026, 1:06 a.m.