Triple
T13864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Front (World War II) |
E277
|
entity |
| Predicate | characterizedBy |
P662
|
FINISHED |
| Object | large-scale tank warfare |
—
|
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: large-scale tank warfare | Statement: [Eastern Front (World War II), characterizedBy, large-scale tank warfare]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterizedBy Context triple: [Eastern Front (World War II), characterizedBy, large-scale tank warfare]
-
A.
describes
Indicates that one entity provides an explanation, representation, or account of another entity or concept.
-
B.
describedIn
Indicates that information about an entity is contained or documented within a specified source, such as a text, document, or media.
-
C.
demographicsCharacteristic
Indicates that one entity serves as a demographic attribute or characteristic (such as age, gender, ethnicity, etc.) that describes or classifies another entity.
-
D.
recognizedAs
Indicates that one entity is acknowledged or accepted as having the identity, role, status, or classification of another entity.
-
E.
demonstratedBy
Indicates that something is shown, proven, or made evident through the actions, behavior, or example of a particular entity.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a240b249788190af8dbf7e80e9c91b |
completed | Feb. 28, 2026, 1:11 a.m. |
| PD | Predicate disambiguation | batch_69a23feae8c481908d8c50faac01fc5c |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a240b1551c81908abcae128ea45d00 |
completed | Feb. 28, 2026, 1:11 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.