Triple
T35533595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | America (Four Continents) |
E1026869
|
entity |
| Predicate | sisterWork |
P183213
|
FINISHED |
| Object | Asia (Four Continents) |
—
|
NE NERFINISHED |
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: Asia (Four Continents) | Statement: [America (Four Continents), sisterWork, Asia (Four Continents)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sisterWork Context triple: [America (Four Continents), sisterWork, Asia (Four Continents)]
-
A.
sisterLine
Indicates that one entity is a sister of another within a family or genealogical relationship.
-
B.
hasSister
Indicates that one entity is the sister of another entity.
-
C.
sisterShow
Indicates that two shows are related as sister shows, typically sharing common origins, networks, or production ties without one being derived from the other.
-
D.
sibling
Indicates that two entities share at least one parent, making them brothers or sisters to each other.
-
E.
sisterCategory
Indicates a relationship between two categories that share a common parent category, making them parallel or peer categories at the same hierarchical level.
- F. None of above. chosen
Provenance (4 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_69f76dff7e508190b28ceeee770dce23 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79a54aa3c8190b2bb5d790b2d42d4 |
completed | May 3, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69f7961970408190b669cc556e30a608 |
completed | May 3, 2026, 6:38 p.m. |
| PDg | Predicate description generation | batch_69f79a53ccc481908421ae16e69aa8a4 |
completed | May 3, 2026, 6:56 p.m. |
Created at: May 3, 2026, 4:04 p.m.