Triple
T38212807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Hart as Matt Logelin |
E1010600
|
entity |
| Predicate | maritalStatusAfterWifesDeath |
P61663
|
FINISHED |
| Object | widowed |
—
|
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: widowed | Statement: [Kevin Hart as Matt Logelin, maritalStatusAfterWifesDeath, widowed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maritalStatusAfterWifesDeath Context triple: [Kevin Hart as Matt Logelin, maritalStatusAfterWifesDeath, widowed]
-
A.
spouseStatusAfterDeath
chosen
Indicates the marital status or spousal relationship of a person after the death of their spouse.
-
B.
marriedToUntilDeathOfSpouse
Indicates a marital relationship that is intended to remain in effect until the death of one of the spouses.
-
C.
spouseDeath
Indicates that one person's spouse has died, marking the event of the spouse's death in relation to that person.
-
D.
hasMaritalStatusAfterFirstMarriage
Indicates that an entity’s marital status at a given time is the one it holds after its first marriage has occurred.
-
E.
residenceAfterHusbandDeath
Indicates the place where a person resides following the death of their husband.
- F. None of above.
Provenance (3 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_69f76dcdc7708190a5f1751d53f40ffe |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fccbd826708190b5fab12c4236299a |
completed | May 7, 2026, 5:28 p.m. |
| PD | Predicate disambiguation | batch_69fcc58838e08190b8fa54aa5c165f2d |
completed | May 7, 2026, 5:02 p.m. |
Created at: May 3, 2026, 4:30 p.m.