Triple
T3525464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diocese of El Camino Real |
E74527
|
entity |
| Predicate | officeHeldBy |
P537
|
FINISHED |
| Object | Lucinda Ashby |
E391548
|
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: Lucinda Ashby | Statement: [Diocese of El Camino Real, officeHeldBy, Lucinda Ashby]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucinda Ashby Context triple: [Diocese of El Camino Real, officeHeldBy, Lucinda Ashby]
-
A.
Lucinda Ashby
chosen
Lucinda Ashby is an Episcopal bishop who leads the Diocese of El Camino Real in California.
-
B.
Anne Ashmond
Anne Ashmond is a fictional character appearing in the film "Royal Wedding."
-
C.
Joanna Ashby
Joanna Ashby is a phonetician and lexicographer known for her later editorial work on the Cambridge English Pronouncing Dictionary.
-
D.
Ruby Gentry
Ruby Gentry is a 1952 American melodrama film directed by King Vidor, starring Jennifer Jones as a poor Southern woman whose passionate love and social struggles lead to tragedy.
-
E.
Katherine Clifton
Katherine Clifton is a central character in Michael Ondaatje's novel "The English Patient," known for her tragic love affair and its far-reaching consequences during World War II.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad85d0c5488190a3d8e02ebd01a1aa |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc6a8d0c819094d38b9c47fb67b4 |
completed | March 8, 2026, 6:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b503d9643881909737836640c22802 |
completed | March 14, 2026, 6:44 a.m. |
Created at: March 8, 2026, 3:19 p.m.