Triple
T16006172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Susannah Spurgeon |
E388223
|
entity |
| Predicate | founded |
P104
|
FINISHED |
| Object |
Book Fund
The Book Fund was a charitable initiative established to provide Christian literature and support to impoverished pastors and ministers.
|
E1187719
|
NE FINISHED |
How this triple was built (4 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: Book Fund | Statement: [Susannah Spurgeon, founded, Book Fund]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Book Fund Context triple: [Susannah Spurgeon, founded, Book Fund]
-
A.
Buch
Buch is a locality in the Berlin borough of Pankow, known for its historic hospital complex and extensive green spaces on the northeastern edge of the city.
-
B.
الكتاب
الكتاب هو مؤلَّف نحوي كلاسيكي لسيبويه يُعدّ من أهم وأقدم المراجع في النحو العربي.
-
C.
Buchs
Buchs is a municipality in the canton of St. Gallen in northeastern Switzerland, known as an industrial and commercial center near the Liechtenstein border.
-
D.
Date Book
Date Book is a built-in personal information management application for Palm OS devices, used primarily for scheduling appointments and managing calendars.
-
E.
Word Books
Word Books was a Christian publishing company known for producing religious and inspirational literature.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Book Fund Triple: [Susannah Spurgeon, founded, Book Fund]
Generated description
The Book Fund was a charitable initiative established to provide Christian literature and support to impoverished pastors and ministers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Book Fund Target entity description: The Book Fund was a charitable initiative established to provide Christian literature and support to impoverished pastors and ministers.
-
A.
Buch
Buch is a locality in the Berlin borough of Pankow, known for its historic hospital complex and extensive green spaces on the northeastern edge of the city.
-
B.
الكتاب
الكتاب هو مؤلَّف نحوي كلاسيكي لسيبويه يُعدّ من أهم وأقدم المراجع في النحو العربي.
-
C.
Buchs
Buchs is a municipality in the canton of St. Gallen in northeastern Switzerland, known as an industrial and commercial center near the Liechtenstein border.
-
D.
Date Book
Date Book is a built-in personal information management application for Palm OS devices, used primarily for scheduling appointments and managing calendars.
-
E.
Word Books
Word Books was a Christian publishing company known for producing religious and inspirational literature.
- F. None of above. chosen
Provenance (5 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e15800246c8190a298c5f96478c396 |
completed | April 16, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffc3dec0c0819099b9007ad0fc6fb4 |
completed | May 9, 2026, 11:31 p.m. |
| NEDg | Description generation | batch_69ffc49bfa088190a6291f560ca9bdb5 |
completed | May 9, 2026, 11:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffc538a5f0819097ea09f57d3cae35 |
completed | May 9, 2026, 11:37 p.m. |
Created at: April 10, 2026, 4:55 a.m.