Triple
T2758684
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gabo |
E61165
|
entity |
| Predicate | refersToPersonField |
P6979
|
FINISHED |
| Object | literature |
—
|
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: literature | Statement: [Gabo, refersToPersonField, literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refersToPersonField Context triple: [Gabo, refersToPersonField, literature]
-
A.
refersToPerson
Indicates that one entity is making reference to, mentioning, or pointing specifically to a particular person.
-
B.
refersToRole
Indicates that one entity designates, mentions, or points to another entity specifically in its capacity as a role or position.
-
C.
relatedField
chosen
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
D.
appliesToPerson
Indicates that something (such as a rule, condition, or attribute) is relevant or applicable to a specific person.
-
E.
termRelationTo
Indicates a general relational association between one term and another, without specifying the exact nature of that relationship.
- F. None of above.
Provenance (3 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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb8d34f88190a760111fe303cf24 |
completed | March 7, 2026, 8:02 a.m. |
| PD | Predicate disambiguation | batch_69abd82de7f48190acd614f28644c6da |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:57 p.m.