Triple
T24769440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Resígaru |
E619679
|
entity |
| Predicate | knowledgeSource |
P157114
|
FINISHED |
| Object | linguistic field reports |
—
|
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: linguistic field reports | Statement: [Resígaru, knowledgeSource, linguistic field reports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knowledgeSource Context triple: [Resígaru, knowledgeSource, linguistic field reports]
-
A.
knowledgeSourceInUniverse
Indicates that a particular source or repository of knowledge exists or is valid within a specified universe or contextual domain.
-
B.
knowledgeSourceInStory
Indicates that a particular source or origin of information is referenced or used within the context of a story.
-
C.
knowledgeOutput
Indicates that an entity produces, expresses, or makes available knowledge, information, or learned content as an output.
-
D.
earningSource
Indicates that one entity is the origin or provider of another entity’s earnings or income.
-
E.
knowledgeExchange
Indicates a reciprocal sharing or transfer of knowledge, information, or expertise between entities.
- 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_69e2fabd04488190a2d13c97be745a2d |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f410a8dc8081909e2f4b65485a6786 |
completed | May 1, 2026, 2:32 a.m. |
| PD | Predicate disambiguation | batch_69f40ef612c88190ab2f3f08d4a92018 |
completed | May 1, 2026, 2:24 a.m. |
| PDg | Predicate description generation | batch_69f410a001788190a457e41f53aaf90c |
completed | May 1, 2026, 2:32 a.m. |
Created at: April 18, 2026, 4:29 a.m.