Triple
T38625177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linth |
E936985
|
entity |
| Predicate | hasMajorHumanModification |
P61330
|
FINISHED |
| Object | Linth correction |
—
|
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: Linth correction | Statement: [Linth, hasMajorHumanModification, Linth correction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorHumanModification Context triple: [Linth, hasMajorHumanModification, Linth correction]
-
A.
hasHumanModification
chosen
Indicates that an entity has been altered, influenced, or modified as a result of human activity or intervention.
-
B.
hasModificationComparedTo
Indicates that one entity differs from another by having a specific change, adjustment, or alteration relative to it.
-
C.
hasMajorDelta
Indicates that there is a significant or substantial change or difference between two compared entities or states.
-
D.
hasMajor
Indicates that an entity (typically a person or student) has a specific primary field of academic study or specialization.
-
E.
hasMajorWork
Indicates that an entity (typically a person, creator, or organization) is associated with a significant or principal work they produced or are best known for.
- 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_69f76ed403208190b862dc795171353f |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a2026248190b894436a578d79ac |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:32 p.m.