Triple
T9087852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larry Underwood |
E217803
|
entity |
| Predicate | followerOf |
P21428
|
FINISHED |
| Object | Mother Abagail |
E192767
|
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: Mother Abagail | Statement: [Larry Underwood, followerOf, Mother Abagail]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mother Abagail Context triple: [Larry Underwood, followerOf, Mother Abagail]
-
A.
Mother Abagail
chosen
Mother Abagail is a prophetic, 108-year-old spiritual leader who guides the forces of good in Stephen King’s post-apocalyptic novel "The Stand."
-
B.
Sarah Good
Sarah Good was one of the first women accused and executed for witchcraft during the 1692 Salem witch trials in colonial Massachusetts.
-
C.
Prudence Wakefield
Prudence Wakefield was the mother of the English scholar and controversialist Gilbert Wakefield.
-
D.
Anna Brewster
Anna Brewster is an English actress and model known for her roles in film and television, including period dramas and independent features.
-
E.
Abigail Ames
Abigail Ames is a person notable enough to be specifically cited as a bearer of the surname Ames.
- 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_69ca83d8ab5881909d8fddae363b32b1 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc965646408190b041ab0e2d5dbc94 |
completed | April 1, 2026, 3:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d02ffa9fb88190ab088be46b566ae8 |
completed | April 3, 2026, 9:24 p.m. |
Created at: March 30, 2026, 7:13 p.m.