Triple
T35748299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goolagong-Cawley |
E1033245
|
entity |
| Predicate | hasMarriedNamePart |
P14292
|
FINISHED |
| Object | Cawley |
E2153624
|
NE 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: Cawley | Statement: [Goolagong-Cawley, hasMarriedNamePart, Cawley]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarriedNamePart Context triple: [Goolagong-Cawley, hasMarriedNamePart, Cawley]
-
A.
hasMarriedSurname
chosen
Indicates that a person’s current surname is the one they adopted through marriage.
-
B.
laterMarriedName
Indicates that the referenced name is a surname or full name a person adopted after a later marriage, replacing or succeeding their previous name.
-
C.
marriedBy
Indicates that one entity is the officiant or authority who performs and formalizes the marriage of another entity.
-
D.
marriedToFrom
Indicates that one entity is married to another, with the direction emphasizing the spouse or origin of the marital relationship.
-
E.
marriedIn
Indicates that two entities entered into a marital relationship at a specific place or within a particular jurisdiction.
- F. None of above.
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_69f76e119d508190a3873cb302063832 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a02f847b9848190a9fedbc411ae0918 |
completed | May 12, 2026, 9:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a389156ca948190a3c9435aea9082db |
completed | June 22, 2026, 1:35 a.m. |
| PD | Predicate disambiguation | batch_6a02f556860c8190b2995433fa05fdd0 |
completed | May 12, 2026, 9:39 a.m. |
Created at: May 3, 2026, 4:06 p.m.