Triple
T14737012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benedict Turretin |
E346237
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Turretin |
E337885
|
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: Turretin | Statement: [Benedict Turretin, familyName, Turretin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Turretin Context triple: [Benedict Turretin, familyName, Turretin]
-
A.
Turretin
chosen
Turretin is a notable Reformed theologian surname most famously associated with Francis Turretin, a 17th-century Genevan scholastic theologian.
-
B.
The Turret
The Turret is a novel by British author Margery Sharp, best known for its blend of sharp social observation and character-driven storytelling.
-
C.
Crannon
Crannon was an ancient city of Thessaly in Greece, historically significant as a regional center in the Pelasgiotis district.
-
D.
Talbo
Talbo is the surname of Dolly Talbo, a character whose last name identifies her within her fictional or narrative family lineage.
-
E.
The Fortress
The Fortress is a South Korean historical drama film depicting the Joseon court’s struggle for survival during the Qing invasion, directed by Hwang Dong-hyuk.
- 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec73114cc819088e1101b689fc70b |
completed | April 14, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb90378481909a3083680f11101c |
completed | May 8, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:29 a.m.