Triple
T15871817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hour of Power |
E384846
|
entity |
| Predicate | presenter |
P83
|
FINISHED |
| Object | Sheila Schuller Coleman |
E1186483
|
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: Sheila Schuller Coleman | Statement: [Hour of Power, presenter, Sheila Schuller Coleman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sheila Schuller Coleman Context triple: [Hour of Power, presenter, Sheila Schuller Coleman]
-
A.
Sheila Schuller Coleman
chosen
Sheila Schuller Coleman is an American pastor and author best known for her leadership role at the Crystal Cathedral and as the daughter of televangelist Robert H. Schuller.
-
B.
Anita Coleman
Anita Coleman is a fictional character known as a relative of Dino Brewster in the "Need for Speed" film universe.
-
C.
Mary Sue Coleman
Mary Sue Coleman is an American chemist and academic leader best known for serving as president of the University of Michigan and the University of Iowa and for her influential role in higher education policy.
-
D.
Diane Bemus
Diane Bemus is an individual whose birth name is Diane Bemus and who is also known as Diane Bemus Patrick.
-
E.
Ann Coleman
Ann Coleman was a key benefactor and restorer of France’s Château de Villandry, helping to preserve and revive the historic Renaissance estate and its renowned gardens.
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e155fa1aac81908e4b86abedf295ca |
completed | April 16, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3b8fe488190b9155100c647a948 |
completed | May 9, 2026, 11:31 p.m. |
Created at: April 10, 2026, 4:50 a.m.