Triple
T23833348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lovey Howell |
E589572
|
entity |
| Predicate | relationshipTypeWithThurstonHowellIII |
P153782
|
FINISHED |
| Object | devoted but comically indulgent spouse |
—
|
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: devoted but comically indulgent spouse | Statement: [Lovey Howell, relationshipTypeWithThurstonHowellIII, devoted but comically indulgent spouse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipTypeWithThurstonHowellIII Context triple: [Lovey Howell, relationshipTypeWithThurstonHowellIII, devoted but comically indulgent spouse]
-
A.
relationshipType
Indicates the specific kind of relationship that exists between two or more entities.
-
B.
relationshipTypeWithSassi
Indicates the specific type or nature of the relationship that an entity has with Sassi.
-
C.
relationshipToHumans
Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
-
D.
relationshipTestedBy
Indicates that a relationship between entities has been examined or evaluated by a specified agent, method, or test.
-
E.
relationshipTypeWithTaystee
Indicates the specific nature or category of relationship that an entity has with Taystee.
- 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_69e25d1922d481909cab567c06a802ab |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1c7f7aa488190b1bc5cab77a11123 |
completed | April 29, 2026, 8:57 a.m. |
| PD | Predicate disambiguation | batch_69f156036ad48190bc2ffdaf39218bcb |
completed | April 29, 2026, 12:51 a.m. |
| PDg | Predicate description generation | batch_69f158b0e320819090b947ee7eb14116 |
completed | April 29, 2026, 1:02 a.m. |
Created at: April 17, 2026, 8:06 p.m.