Triple
T22977924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sara Gruen |
E571375
|
entity |
| Predicate | Water for Elephants |
P150476
|
FINISHED |
| Object | instanceOf:bestselling novel |
—
|
LITERAL 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: instanceOf:bestselling novel | Statement: [Sara Gruen, Water for Elephants, instanceOf:bestselling novel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: Water for Elephants Context triple: [Sara Gruen, Water for Elephants, instanceOf:bestselling novel]
-
A.
The Tourist
Indicates a relationship where an entity is characterized as a visitor or traveler temporarily present in a place rather than a permanent resident.
-
B.
التيجان والأوسمة
Indicates the relationship of conferring, wearing, or possessing crowns and decorations (such as medals or orders of honor) as marks of rank, distinction, or recognition.
-
C.
تاريخ الزواج
Indicates the date on which a marriage took place between the related entities.
-
D.
الزوجة
Indicates that one entity is the wife (spouse in a marital relationship) of another entity.
-
E.
تذكر وصف العذاب
Indicates mentioning or recalling a description of the torment or punishment.
- F. None of above. chosen
Provenance (4 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_69e245b3c50481908bb3741ec9f40862 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18292f3788190ab4e9d559e0070c8 |
completed | April 29, 2026, 4:01 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
| PDg | Predicate description generation | batch_69ef538a115081908982597f79355840 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:49 p.m.