Triple
T30934173
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry Mudd |
E788073
|
entity |
| Predicate | relationshipTypeWithStellaMudd |
P207323
|
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: [Harry Mudd, relationshipTypeWithStellaMudd, estranged]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithStellaMudd Context triple: [Harry Mudd, relationshipTypeWithStellaMudd, estranged]
-
A.
relationshipTypeWithSassi
Indicates the specific type or nature of the relationship that an entity has with Sassi.
-
B.
relationshipTypeWith Mona Stangley
Indicates the specific type or nature of relationship that an entity has with Mona Stangley.
-
C.
relationshipTypeWithTaystee
Indicates the specific nature or category of relationship that an entity has with Taystee.
-
D.
relationshipToAlice
Indicates the specific type of relationship or connection that an entity has with Alice.
-
E.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
- 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_69f224c0b7fc819090cb89df60d23653 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 8:52 p.m.