Triple
T32669506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baroness Morgan of Cotes |
E835249
|
entity |
| Predicate | titleHolderCommonName |
P142563
|
FINISHED |
| Object | Nicky Morgan |
—
|
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: Nicky Morgan | Statement: [Baroness Morgan of Cotes, titleHolderCommonName, Nicky Morgan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleHolderCommonName Context triple: [Baroness Morgan of Cotes, titleHolderCommonName, Nicky Morgan]
-
A.
titleHolderName
Indicates the name of the person or entity that holds a particular title or position.
-
B.
titleHolderFullName
Indicates the full personal name of the entity that holds a particular title or position.
-
C.
titleHolderGivenName
Indicates that the predicate specifies the given (first) name of the person who holds a particular title.
-
D.
titleHolderLabel
Indicates the entity that currently or formerly holds a specified title, position, or honor.
-
E.
titleHolderKnownAs
chosen
Indicates that the person holding a particular title is commonly referred to or known by a specified name or alias.
- 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_69f349303ccc8190a70d0f6e8a21d3fb |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fec25f0fc48190b87ab1f9cd1eb0de |
completed | May 9, 2026, 5:13 a.m. |
| PD | Predicate disambiguation | batch_69fec079a770819098df7cc3049df954 |
completed | May 9, 2026, 5:04 a.m. |
Created at: May 1, 2026, 1:09 a.m.