Triple
T8645378
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tami-Lynn |
E204759
|
entity |
| Predicate | hasMaritalStatusWithTedInTed2 |
P56596
|
FINISHED |
| Object | married |
—
|
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: married | Statement: [Tami-Lynn, hasMaritalStatusWithTedInTed2, married]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMaritalStatusWithTedInTed2 Context triple: [Tami-Lynn, hasMaritalStatusWithTedInTed2, married]
-
A.
parentsMarriageStatus
Indicates the marital status relationship between an individual’s parents (e.g., married, divorced, separated, never married).
-
B.
hasMaritalRelationshipType
chosen
Indicates the specific type or nature of the marital relationship that exists between two entities.
-
C.
hasMarriage
Indicates a marital relationship exists between the two entities, specifying that they are or were legally married to each other.
-
D.
spouseStatusAtMarriage
Indicates the marital status each partner held at the time their marriage to one another was formed.
-
E.
marital status
Indicates the legal or social state of a person’s marriage-related relationship, such as being single, married, divorced, or widowed.
- 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_69ca834ca1c88190a11ffb0200342fac |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc479999c881908c0c4e01c07d02d4 |
completed | March 31, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69cc455d6d448190a2da2a319ac78c37 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:28 p.m.