Triple
T1492713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umm Salama |
E29616
|
entity |
| Predicate | wasMarriedBeforeProphet |
P28605
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Umm Salama, wasMarriedBeforeProphet, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasMarriedBeforeProphet Context triple: [Umm Salama, wasMarriedBeforeProphet, true]
-
A.
marriageToMuhammadType
Indicates a marital relationship in which the person is (or was) married to Muhammad, specifying that the marriage is to the individual identified as Muhammad.
-
B.
marriedAfter
Indicates that one marriage occurred later in time than another specified marriage.
-
C.
hasSpouseInTradition
Indicates that one entity is recognized as the spouse of another according to a specified cultural, religious, or legal tradition.
-
D.
firstWifeOf
Indicates that one person is the first woman to have been married to another person.
-
E.
marriedInto
Indicates that one entity became connected to another’s family or group through marriage, rather than by birth or prior membership.
- 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6c4f0c88190a97ba4910c1a5d85 |
completed | March 1, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69a4c48902808190a8028d359bcf123e |
completed | March 1, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69a4c52c703c8190a56389b09d97659f |
completed | March 1, 2026, 11:01 p.m. |
Created at: March 1, 2026, 8:12 p.m.