Triple
T27088911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thatcher Grey |
E686106
|
entity |
| Predicate | relationshipStatusWithMeredith |
P199436
|
FINISHED |
| Object | estranged |
—
|
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: estranged | Statement: [Thatcher Grey, relationshipStatusWithMeredith, estranged]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipStatusWithMeredith Context triple: [Thatcher Grey, relationshipStatusWithMeredith, estranged]
-
A.
relationshipToMeredithGrey
Indicates the specific interpersonal or familial relationship that an entity has with Meredith Grey.
-
B.
relationshipStatusWithMichael
Indicates the type or state of the relationship that an entity currently has with Michael.
-
C.
relationshipStatusWithMarnie
Indicates the nature or current state of the relationship that an entity has with Marnie.
-
D.
relationshipToMichelle
Indicates the specific type of relationship or connection that an entity has to Michelle.
-
E.
relationshipWithMargo
Indicates that an entity has some form of relationship or connection with Margo.
- 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_69ef148940ec819097b5c20fbfbf7c81 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69ff397e19a88190a945b826159f5290 |
completed | May 9, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69ff392400d0819088d30d08d4a774bd |
completed | May 9, 2026, 1:39 p.m. |
| PDg | Predicate description generation | batch_69ff397d6a2081908fa8f62e8902421b |
completed | May 9, 2026, 1:41 p.m. |
Created at: April 27, 2026, 8:39 a.m.