Triple
T14229921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Troisier's sign |
E352724
|
entity |
| Predicate | isStronglyAssociatedWith |
P2830
|
FINISHED |
| Object | gastric cancer |
—
|
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: gastric cancer | Statement: [Troisier's sign, isStronglyAssociatedWith, gastric cancer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isStronglyAssociatedWith Context triple: [Troisier's sign, isStronglyAssociatedWith, gastric cancer]
-
A.
isAssociatedWith
chosen
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
-
B.
notablyAssociatedWith
Indicates that one entity is prominently or distinctively connected with another in a way that is especially noteworthy or remarkable.
-
C.
notStronglyAssociatedWith
Indicates that two entities have little to no meaningful or statistically significant relationship or connection with each other.
-
D.
positionAssociatedWith
Indicates a relationship where a specific role, job, or position is linked or connected to a particular entity, context, or resource.
-
E.
associationWithHumans
Indicates a general relationship, connection, or involvement between an entity and one or more humans.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de622b89fc8190af08dab9e1976759 |
completed | April 14, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69de05bf069c8190b69f00f00f5eb126 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:07 a.m.