Triple
T22002082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rosa Coldfield |
E543350
|
entity |
| Predicate | relationshipToEllenColdfield |
P146235
|
FINISHED |
| Object | younger sister |
—
|
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: younger sister | Statement: [Rosa Coldfield, relationshipToEllenColdfield, younger sister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToEllenColdfield Context triple: [Rosa Coldfield, relationshipToEllenColdfield, younger sister]
-
A.
relationshipToAuntEller
Indicates the specific familial relationship that an entity has to Aunt Eller (e.g., whether and how they are related to her).
-
B.
relationshipToKateKeller
Indicates the specific familial, social, or interpersonal connection that one entity has to Kate Keller.
-
C.
relationshipWithElliotGarfield
Indicates a relationship or connection that an entity has with Elliot Garfield.
-
D.
relationshipToKellers
Indicates the type of personal or familial relationship an entity has with the Kellers.
-
E.
relationshipToMichelle
Indicates the specific type of relationship or connection that an entity has to Michelle.
- 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1276bf2a48190910d9c27f1c5e74f |
completed | April 28, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69e6f62dc9d88190ae387f145f9528de |
completed | April 21, 2026, 3:59 a.m. |
| PDg | Predicate description generation | batch_69e6fad4a540819096cdd5ea08527220 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 8:20 p.m.