Triple
T35142583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ursula Buffay |
E1014733
|
entity |
| Predicate | relationshipToPhoebeBuffay |
P206850
|
FINISHED |
| Object | older twin 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: older twin sister | Statement: [Ursula Buffay, relationshipToPhoebeBuffay, older twin sister]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToPhoebeBuffay Context triple: [Ursula Buffay, relationshipToPhoebeBuffay, older twin sister]
-
A.
relationshipToRebecca
Indicates the specific type of relationship or connection an entity has to Rebecca.
-
B.
relationshipToMichelle
Indicates the specific type of relationship or connection that an entity has to Michelle.
-
C.
relationshipToBeth
Indicates the specific type of relationship or connection that an entity has to Beth.
-
D.
relationshipToSheldonCooper
Indicates the specific interpersonal or familial connection that an entity has to Sheldon Cooper.
-
E.
relationshipToBobBelcher
Indicates the specific familial, social, or professional relationship that one entity has to Bob Belcher.
- 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_69f76dda7c108190a2ffd93eb6c341a7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a016960819093ed4990fb4d9d36 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82179081908325a59b8539b3a8 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:02 p.m.