Triple
T34689914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bridey Murphy |
E890862
|
entity |
| Predicate | allegedMaidenName |
P36176
|
FINISHED |
| Object | Bridget Kathleen Murphy |
—
|
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: Bridget Kathleen Murphy | Statement: [Bridey Murphy, allegedMaidenName, Bridget Kathleen Murphy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allegedMaidenName Context triple: [Bridey Murphy, allegedMaidenName, Bridget Kathleen Murphy]
-
A.
maidenNameOf
chosen
Indicates that one person’s original family surname before marriage is the maiden name of another person.
-
B.
motherName
Indicates that the predicate specifies the personal name of an entity’s mother.
-
C.
motherAlias
Indicates that one entity is an alternative name, label, or identifier used to refer to a mother in relation to another entity.
-
D.
originalNameGivenByMother
Indicates that the name in question is the original name assigned to an individual specifically by their mother.
-
E.
motherLegalName
Indicates that the object is the full legal name of the subject's mother.
- 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_69f349db7ab8819086808e833f472871 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 1, 2026, 2:05 a.m.