Triple
T409838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peter the Great |
E9463
|
entity |
| Predicate | interestedIn |
P1074
|
FINISHED |
| Object | shipbuilding |
—
|
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: shipbuilding | Statement: [Peter the Great, interestedIn, shipbuilding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: interestedIn Context triple: [Peter the Great, interestedIn, shipbuilding]
-
A.
representsInterestOf
chosen
Indicates that one entity expresses, holds, or embodies an interest, concern, or stake in another entity or subject.
-
B.
loveInterest
Indicates that one entity is the romantic object of affection or attraction for another entity.
-
C.
introducedTo
Indicates that one entity caused or facilitated a first meeting or formal presentation between another entity and a third party.
-
D.
isPopularWith
Indicates that one entity is well-liked, favored, or widely accepted by another entity or group.
-
E.
frequentlyDiscussedIn
Indicates that a topic, subject, or entity is often the focus of conversation, debate, or mention within a particular context or medium.
- 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_69a2e80111fc8190961d5b7c6154123f |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2ed31681c8190ac32334562fb17fd |
completed | Feb. 28, 2026, 1:27 p.m. |
| PD | Predicate disambiguation | batch_69a2e9737694819080fde9adcc1aa4d4 |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.