Triple
T35367580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shigeru Nakamura |
E1021675
|
entity |
| Predicate | ambiguousRefersTo |
P104889
|
FINISHED |
| Object | multiple individuals |
—
|
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: multiple individuals | Statement: [Shigeru Nakamura, ambiguousRefersTo, multiple individuals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ambiguousRefersTo Context triple: [Shigeru Nakamura, ambiguousRefersTo, multiple individuals]
-
A.
alsoRefersTo
Indicates that one term, label, or identifier is used as an alternative designation for the same entity or concept as another.
-
B.
oftenRefersTo
Indicates that one entity is frequently used to mention, denote, or reference another entity in common usage or context.
-
C.
abbreviationRefersTo
Indicates that an abbreviation stands for or denotes the full form or concept it is associated with.
-
D.
refersSpecificallyTo
Indicates that one entity makes an explicit, precise reference to another particular entity, distinguishing it from more general or ambiguous references.
-
E.
ambiguity
chosen
Indicates that there is uncertainty, vagueness, or multiple possible interpretations in the relationship or action between entities.
- 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_69f76df000488190ab7c97f565677055 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.