Triple
T8085561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Bennett series |
E188721
|
entity |
| Predicate | protagonistFamilyStatus |
P80421
|
FINISHED |
| Object | widower |
—
|
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: widower | Statement: [Michael Bennett series, protagonistFamilyStatus, widower]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protagonistFamilyStatus Context triple: [Michael Bennett series, protagonistFamilyStatus, widower]
-
A.
protagonistSocialStatus
Indicates the social standing or class position held by the story’s main character in relation to others in their society.
-
B.
macroFamilyStatus
Indicates the broad genealogical relationship between languages or language families at the macro-family level.
-
C.
hasProtagonistRelationship
Indicates that there exists a central, story-driving relationship involving the protagonist and another entity within a narrative.
-
D.
householdStatus
Indicates the type or condition of a person’s living arrangement within a household, such as their role, membership, or current residency status.
-
E.
familyOf
Indicates a familial relationship exists between the entities, such as by blood, marriage, or adoption.
- 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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb415f73808190b69db386b447062e |
completed | March 31, 2026, 3:37 a.m. |
| PD | Predicate disambiguation | batch_69cb04a14cd88190a79ed26cbeec1c33 |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14be17208190bb51c3dfcb613f20 |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:29 p.m.