Triple
T967899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seven Seals |
E20877
|
entity |
| Predicate | secondSealAssociatedWith |
P22271
|
FINISHED |
| Object | war |
—
|
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: war | Statement: [Seven Seals, secondSealAssociatedWith, war]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondSealAssociatedWith Context triple: [Seven Seals, secondSealAssociatedWith, war]
-
A.
usedSeal
Indicates that an entity has applied or employed a seal (e.g., for closure, authentication, or protection) on another entity.
-
B.
laterSignatory
Indicates that one party signed or agreed to something at a later time than another specified party.
-
C.
seal
Indicates that an agent closes or fastens something so that it is securely shut and often airtight or watertight.
-
D.
secondLetter
Indicates that one entity is the second letter (in sequence or position) of another entity, typically a string or word.
-
E.
departmentSeal
Indicates that one entity serves as the official seal or emblem representing a particular department.
- 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_69a493b33d2c81909c52c369d3ca8436 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b43549008190a4d65efdc3bda520 |
completed | March 1, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69a4b2a42c1481908d940cbe0aefdd3b |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b36064a48190b85c402f32cbadd1 |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:40 p.m.