Triple
T29783719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donald P. Bellisario |
E756199
|
entity |
| Predicate | maritalStatusWithLynnHalpern |
P169694
|
FINISHED |
| Object | divorced |
—
|
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: divorced | Statement: [Donald P. Bellisario, maritalStatusWithLynnHalpern, divorced]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maritalStatusWithLynnHalpern Context triple: [Donald P. Bellisario, maritalStatusWithLynnHalpern, divorced]
-
A.
hasMaritalStatusAtEnd
Indicates that an entity possesses a specific marital status at the end of a given period, event, or reference time.
-
B.
marriageStatusWithHaroldsonLafayetteHunt
Indicates the marital relationship status that an entity has with Haroldson Lafayette Hunt.
-
C.
hasAuthorMarriedName
Indicates that an author’s married surname or full married name is associated with them, typically differing from their birth or maiden name.
-
D.
marriageStatusWithLonChaney
Indicates the marital relationship status that an entity has (or had) with Lon Chaney.
-
E.
maritalStatusInDisguise
Indicates that an entity’s true marital status is being concealed or misrepresented, typically appearing different from what it actually is.
- 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_69f22451fb748190bbdbab401280affb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f68048391c8190abe6580678f8a9ef |
completed | May 2, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f7e116c819099aec724e9ef3763 |
completed | May 2, 2026, 10:49 p.m. |
Created at: April 29, 2026, 5:07 p.m.