Triple
T37246468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Essie Carmichael |
E923867
|
entity |
| Predicate | lastNameAfterMarriage |
P99359
|
FINISHED |
| Object | Carmichael |
—
|
NE NERFINISHED |
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: Carmichael | Statement: [Essie Carmichael, lastNameAfterMarriage, Carmichael]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lastNameAfterMarriage Context triple: [Essie Carmichael, lastNameAfterMarriage, Carmichael]
-
A.
laterMarriedName
chosen
Indicates that the referenced name is a surname or full name a person adopted after a later marriage, replacing or succeeding their previous name.
-
B.
hasMarriedSurname
Indicates that a person’s current surname is the one they adopted through marriage.
-
C.
maidenNameOf
Indicates that one person’s original family surname before marriage is the maiden name of another person.
-
D.
hasFamilyNameAfterSecondMarriage
Indicates that an entity’s family name is the one adopted following their second marriage.
-
E.
marriedAfter
Indicates that one marriage occurred later in time than another specified marriage.
- 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_69f76eaabb4c819093b751b139dad551 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb4134225081909fd60703b8cae397 |
completed | May 6, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69fb35bf767081908de8345358ca7f44 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:15 p.m.